[Federal Register Volume 70, Number 66 (Thursday, April 7, 2005)]
[Notices]
[Pages 17766-17817]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 05-6642]



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Part II





Environmental Protection Agency





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Notice of Availability; Documents Entitled Guidelines for Carcinogen 
Risk Assessment and Supplemental Guidance for Assessing Susceptibility 
From Early-Life Exposure to Carcinogens; Notices

  Federal Register / Vol. 70, No. 66 / Thursday, April 7, 2005 / 
Notices  

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ENVIRONMENTAL PROTECTION AGENCY

[FRL-7895-2]


Notice of Availability of the Document Entitled Guidelines for 
Carcinogen Risk Assessment

AGENCY: U.S. Environmental Protection Agency (EPA).

ACTION: Notice of availability of final document.

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SUMMARY: This Notice announces the availability of the final document, 
Guidelines for Carcinogen Risk Assessment (EPA/630/P-03/001F), 
hereafter referred to as the Guidelines. These Guidelines were 
developed as part of an Agency-wide guidelines development program by a 
Technical Panel of the U.S. EPA's Risk Assessment Forum, which was 
composed of scientists from throughout the Agency. Selected drafts were 
peer reviewed internally by the U.S. EPA's Science Advisory Board, and 
by experts from universities, environmental groups, industry and other 
governmental agencies. The Guidelines were also subjected to several 
public comment periods. Issuance of these final Guidelines fulfills 
EPA's obligations under section 112(o) (7) of the Clean Air Act.

DATES: The Guidelines are available for use by EPA risk assessors as 
March 29, 2005.

ADDRESSES: This Notice contains the full Guidelines document. The 
Guidelines also are available electronically through the EPA Web site 
at http://www.epa.gov/cancerguidelines. A limited number of paper and 
CDROM copies will be available from the EPA's National Service Center 
for Environmental Publications (NSCEP), P.O. Box 42419, Cincinnati, OH 
45242; telephone: (800) 490-9198 or (513) 489-8190; facsimile: (513) 
489-8695. Please provide your name, mailing address and the title and 
number of the requested EPA publication (EPA/630/P-03-001F). 
Additionally, copies of the Guidelines will be available for inspection 
at EPA headquarters and regional libraries, through the U.S. Government 
Depository Library program.

FOR FURTHER INFORMATION CONTACT: Dr. William P. Wood, Risk Assessment 
Forum, National Center for Environmental Assessment (8601D), U.S. 
Environmental Protection Agency, Washington DC 20460, telephone: (202) 
564-3361; facsimile: (202) 565-0062; or e-mail: 
[email protected].

SUPPLEMENTARY INFORMATION: In the 1983 Risk Assessment in the Federal 
Government: Managing the Process, the National Academy of Sciences 
recommended that Federal regulatory agencies establish ``inference 
guidelines'' to promote consistency and technical quality in risk 
assessment, and to ensure that the risk assessment process is 
maintained as a scientific effort separate from risk management. A task 
force within EPA accepted that recommendation and requested that EPA 
scientists begin to develop such guidelines. In 1984, EPA scientists 
began work on risk assessment guidelines for carcinogenicity, 
mutagenicity, suspect developmental toxicants, chemical mixtures and 
exposure assessment. Following extensive scientific and public review, 
these five guidelines were issued on September 24, 1986 (51 FR 33992-
34054). Since 1986, additional risk assessment guidelines have been 
developed, revised and supplemented.
    EPA continues to revisit the guidelines as experience and 
scientific consensus evolve. In 1996, the Agency published proposed 
revisions to EPA's 1986 cancer guidelines for public comment. Since the 
1996 proposal, the document has undergone extensive public comment and 
scientific peer review, including three reviews by EPA's Science 
Advisory Board (SAB) in February 1997, January 1999 and July 1999. The 
July 1999 review panel was supplemented by the EPA Children's Health 
Protection Advisory Committee. Public comments were received concurrent 
to each of these reviews. In 2001 (66 FR 59593, November 29, 2001) an 
additional public comment period was held requesting new information 
gained through the use of the July 1999 draft final revised guidelines 
on issues including, but not limited to, the nature and use of default 
assumptions; definition and application of hazard descriptors; 
identification of carcinogenic mode(s) of action and, in particular, 
consideration of relevancy for children (e.g., the potential for 
differential life stage susceptibility); and guidance on the use of the 
margin of exposure analysis. The notice also announced that the July 
1999 draft final revised guidelines would serve as EPA's interim 
guidance to EPA risk assessors preparing cancer risk assessment, until 
the issuance of final guidelines. In May 2003 EPA made available for 
public comment a revised draft of the guidelines, and in February 2005 
the guidelines underwent interagency review. The final Guidelines 
issued today are based, in part, upon the recommendations derived from 
public comments, workshops and recommendations of the SAB.
    CAA section 112(o)(7) provides ``[t]he Administrator shall 
consider, but need not adopt, the recommendations contained in the 
report of the National Academy of Sciences prepared pursuant to this 
subsection and the views of the Science Advisory Board, with respect to 
such report. Prior to the promulgation of any standard under [CAA 
section 112(f)], and after notice and opportunity for comment, the 
Administrator shall publish revised Guidelines for Carcinogenic Risk 
Assessment or a detailed explanation of the reasons that any 
recommendations contained in the report of the National Academy of 
Sciences will not be implemented.''
    In response to CAA section 112(o)(7), the 1994 National Research 
Council (NRC) report, and continuing developments in the science of 
cancer risk assessment, EPA began the process of revising its 
Guidelines for Carcinogen Risk Assessment. Revisions to the Guidelines 
were intended to make greater use of the increasing scientific 
understanding of the mechanisms that underlie the carcinogenic process. 
Several drafts of revisions to the Guidelines have been subject to 
extensive public comment and scientific peer review, including three 
reviews by EPA's SAB, as discussed above. EPA considered the 1994 
recommendations of the NRC on the Guidelines. EPA's approach to those 
NRC recommendations is reflected in the Guidelines. Draft EPA responses 
to the NRC recommendations were presented in the preamble to the 1996 
draft of these revised Guidelines (61 FR 18003, April 23, 1996). By 
issuing the final Guidelines which address the recommendations of the 
NRC, EPA has fulfilled its responsibilities under CAA section 
112(o)(7).

Features of the Guidelines

    The Guidelines are intended to make greater use of the increasing 
scientific understanding of the mechanisms that underlie the 
carcinogenic process. The final guidelines include discussions of all 
of the four steps of the risk assessment process and provide guidance 
to risk assessors on these steps. In applying these principles to the 
development of these Guidelines, the following key issues were 
highlighted: use of default options, the consideration of mode of 
action, understanding of biological changes, fuller characterization of 
carcinogenic potential, and consideration of differences in 
susceptibility.
    Use of default options--Default options are approaches that EPA can

[[Page 17767]]

apply in risk assessments when scientific information about the effects 
of an agent on human health is unavailable, limited, or of insufficient 
quality. Under the final Guidelines, EPA's approach begins with a 
critical analysis of available information, and then invokes defaults 
if needed to address uncertainty or the absence of critical 
information.
    Consideration of mode of action--Cancer refers to a group of 
diseases involving abnormal, malignant tissue growth. Research has 
revealed that the development of cancer involves a complex series of 
steps and that carcinogens may operate in a number of different ways. 
The final Guidelines emphasize the value of understanding the 
biological changes and how these changes might lead to the development 
of cancer. They also discuss ways to evaluate and use such information, 
including information about an agent's postulated mode of action, or 
the series of steps and processes that lead to cancer formation. Mode-
of-action data, when available and of sufficient quality, may be used 
to draw conclusions about the potency of a chemical, its potential 
effects at low doses, whether findings in animals are relevant to 
humans, and which populations or lifestages may be particularly 
susceptible.
    Fuller characterization of carcinogenic potential--In the final 
Guidelines, an agent's human carcinogenic potential is described in a 
weight-of-evidence narrative. The narrative summarizes the full range 
of available evidence and describes any conditions associated with 
conclusions about an agent's hazard potential. For example, the 
narrative may explain that a chemical appears to be carcinogenic by 
some routes of exposure but not by others (e.g., by inhalation but not 
ingestion). Similarly, a hazard may be attributed to exposures during 
sensitive life-stages of development but not at other times. The 
narrative also summarizes uncertainties and key default options that 
have been invoked. To provide additional clarity and consistency in 
weight-of-evidence narratives, the Guidelines present a set of weight-
of-evidence descriptors that accompany the narratives. The Guidelines 
emphasize that risk managers should consider the full range of 
information in the narratives and not focus exclusively on the 
descriptors. As in the case of the narratives, descriptors may apply 
only to certain routes of exposure, dose ranges and durations of 
exposure.
    Consideration of differences in susceptibility--The Guidelines 
explicitly recognize that variation may exist among people in their 
susceptibility to carcinogens. Some subpopulations may experience 
increased susceptibility to carcinogens throughout their life, such as 
people who have inherited predisposition to certain cancer types or 
reduced capacity to repair genetic damage. Also, during certain 
lifestages the entire population may experience heightened 
susceptibility to carcinogens. In particular, EPA notes that childhood 
may be a lifestage of greater susceptibility for a number of reasons: 
rapid growth and development that occurs prenatally and after birth, 
differences related to an immature metabolic system, and differences in 
diet and behavior patterns that may increase exposure.
    The final Guidelines explicitly call for consideration of possible 
sensitive subpopulations and/or lifestages (such as childhood). 
Therefore, concurrent with release of the final Guidelines, EPA 
published a separate guidance, entitled Supplemental Guidance for 
Assessing Susceptibility from Early-Life Exposure to Carcinogens (EPA/
630/R-03/003F), hereafter referred to as the Supplemental Guidance, 
describing possible approaches that could be used to assess risks 
resulting from early life exposure to potential carcinogens. The 
Supplemental Guidance is separate from the Guidelines so that it may be 
more easily updated in a timely manner given the expected rapid 
evolution of scientific understanding about the effects of early-life 
exposures. Availability of the Supplemental Guidance is announced in a 
separate notice, also published in today's Federal Register.

Risk Assessment Guidelines at EPA

    These Guidelines set forth principles and procedures to guide EPA 
scientists in the conduct of cancer risk assessments and to inform 
Agency decision makers and the public about these procedures. Policies 
in this document are intended as internal guidance for EPA. So risk 
assessors and risk managers at EPA are the primary audience. These 
Guidelines also provide basic information to the public about EPA's 
risk assessment methods. In particular, the Guidelines emphasize that 
risk assessments should be conducted on a case-by-case basis, giving 
full consideration to all relevant scientific information. This 
approach means that Agency experts study scientific information on each 
agent under review and use the most scientifically appropriate 
interpretation to assess risk. The Guidelines also stress that this 
information be fully presented in Agency risk assessment documents, and 
that Agency scientists identify the strengths and weaknesses of each 
assessment by describing uncertainties, assumptions and limitations, as 
well as the scientific basis and rationale for each assessment. The 
Guidelines are formulated in part to bridge gaps in risk assessment 
methodology and data. By identifying these gaps and the importance of 
the missing information to the risk assessment process, EPA wishes to 
encourage research and analysis that will lead to new risk assessment 
methods and data.
    The Guidelines are guidance only. They do not establish any 
substantive ``rules'' under the Administrative Procedure Act or any 
other law and have no binding effect on EPA or any regulated entity, 
but instead will represent a non-binding statement of policy. EPA 
believes that the Guidelines represent a sound and up-to-date approach 
to cancer risk assessment and enhance the application of the best 
available science in EPA's risk assessments. However, EPA cancer risk 
assessments may be conducted differently than envisioned in the 
Guidelines for many reasons, including (but not limited to) new 
information, new scientific understanding or new science policy 
judgment. The science of risk assessment continues to develop rapidly, 
and specific components of the Guidelines may become outdated or may 
otherwise require modification in individual settings. Use of the 
Guidelines in future risk assessments will be based on decisions by EPA 
that approaches from the Guidelines are suitable and appropriate in the 
context of those particular risk assessments. These judgments will be 
tested through peer review, and risk assessments will be modified to 
use different approaches if appropriate.
    Even though the Guidelines are not binding rules, EPA is issuing 
them in a manner consistent with the procedures in the Administrative 
Procedure Act that are generally applicable to rulemaking, including 
providing opportunity for public comment. EPA considered and responded 
to all significant public comments as it prepared the Guidelines and 
will send a copy of the final Guidelines to Congress. EPA certifies 
that the Guidelines will not have a significant impact on a substantial 
number of small entities, because the Guidelines are for the benefit of 
EPA and impose no requirements or costs on small entities.

Implementation

    Beginning today, Guidelines and Supplemental Guidance serve as 
EPA's

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recommendation to Agency risk assessors preparing cancer risk 
assessments. As EPA prepares cancer assessments under the Integrated 
Risk Information System (IRIS) program, as well as in other EPA 
programs, the Agency intends to begin to use the Guidelines and 
Supplemental Guidance. EPA also intends to consider the Guidelines and 
Supplemental Guidance along with other selection factors when EPA 
selects agents for reassessment in annual IRIS agendas (see for 
example, 70 FR 10616, March 4, 2005).

    Dated: March 29, 2005.
Stephen L. Johnson,
Acting Administrator.

Contents

1. Introduction
    1.1. Purpose and Scope of the Guidelines
    1.2. Organization and Application of the Guidelines
    1.2.1. Organization
    1.2.2. Application
    1.3. Key Features of the Cancer Guidelines
    1.3.1. Critical Analysis of Available Information as the 
Starting Point for Evaluation
    1.3.2. Mode of Action
    1.3.3. Weight of Evidence Narrative
    1.3.4. Dose-response Assessment
    1.3.5. Susceptible Populations and Lifestages
    1.3.6. Evaluating Risks from Childhood Exposures
    1.3.7. Emphasis on Characterization
2. Hazard Assessment
    2.1. Overview of Hazard Assessment and Characterization
    2.1.1. Analyses of Data
    2.1.2. Presentation of Results
    2.2. Analysis of Tumor Data
    2.2.1. Human Data
    2.2.1.1. Assessment of Evidence of Carcinogenicity From Human 
Data
    2.2.1.2. Types of Studies
    2.2.1.3. Exposure Issues
    2.2.1.4. Biological Markers
    2.2.1.5. Confounding Actors
    2.2.1.6. Statistical Considerations
    2.2.1.6.1. Likelihood of Observing an Effect
    2.2.1.6.2. Sampling and Other Bias Issues
    2.2.1.6.3. Combining Statistical Evidence Across Studies
    2.2.1.7. Evidence for Causality
    2.2.2. Animal Data
    2.2.2.1. Long-term Carcinogenicity Studies
    2.2.2.1.1. Dosing Issues
    2.2.2.1.2. Statistical Considerations
    2.2.2.1.3. Concurrent and Historical Controls
    2.2.2.1.4. Assessment of Evidence of Carcinogenicity From Long-
term Animal Studies
    2.2.2.1.5. Site Concordance
    2.2.2.2. Perinatal Carcinogenicity Studies
    2.2.2.3. Other Studies
    2.2.3. Structural Analogue Data
    2.3. Analysis of Other Key Data
    2.3.1. Physicochemical Properties
    2.3.2. Structure-Activity Relationships
    2.3.3. Comparative Metabolism and Toxicokinetics
    2.3.4. Toxicological and Clinical Findings
    2.3.5. Events Relevant to Mode of Carcinogenic Action
    2.3.5.1. Direct DNA-Reactive Effects
    2.3.5.2. Indirect DNA Effects or Other Effects on Genes/Gene 
Expression
    2.3.5.3. Precursor Events and Biomarker Information
    2.3.5.4. Judging Data
    2.4. Mode of Action--General Considerations and Framework for 
Analysis
    2.4.1. General Considerations
    2.4.2. Evaluating a Hypothesized Mode of Action
    2.4.2.1. Peer Review
    2.4.2.2. Use of the Framework
    2.4.3. Framework for Evaluating Each Hypothesized Carcinogenic 
Mode of Action
    2.4.3.1. Description of the Hypothesized Mode of Action
    2.4.3.2. Discussion of the Experimental Support for the 
Hypothesized Mode of Action
    2.4.3.3. Consideration of the Possibility of Other Modes of 
Action
    2.4.3.4. Conclusions About the Hypothesized Mode of Action
    2.4.4. Evolution with Experience
    2.5. Weight of Evidence Narrative
    2.6. Hazard Characterization
3. Dose-Response Assessment
    3.1. Analysis of Dose
    3.1.1. Standardizing Different Experimental Dosing Regimens
    3.1.2. Toxicokinetic Data and Modeling
    3.1.3. Cross-species Scaling Procedures
    3.1.3.1. Oral Exposures
    3.1.3.2. Inhalation Exposures
    3.1.4. Route Extrapolation
    3.2. Analysis in the Range of Observation
    3.2.1. Epidemiologic Studies
    3.2.2. Toxicodynamic (``Biologically Based'') Modeling
    3.2.3. Empirical Modeling (``Curve Fitting'')
    3.2.4. Point of Departure (POD)
    3.2.5. Characterizing the POD: The POD Narrative
    3.2.6. Relative Potency Factors
    3.3. Extrapolation to Lower Doses
    3.3.1. Choosing an Extrapolation Approach
    3.3.2. Extrapolation Using a Toxicodynamic Model
    3.3.3. Extrapolation Using a Low-dose Linear Model
    3.3.4. Nonlinear Extrapolation to Lower Doses
    3.3.5. Comparing and Combining Multiple Extrapolations
    3.4. Extrapolation to Different Human Exposure Scenarios
    3.5. Extrapolation to Susceptible Populations and Lifestages
    3.6. Uncertainty
    3.7. Dose-Response Characterization
4. Exposure Assessment
    4.1. Defining the Assessment Questions
    4.2. Selecting or Developing the Conceptual and Mathematical 
Models
    4.3. Collecting Data or Selecting and Evaluating Available Data
    4.3.1. Adjusting Unit Risks for Highly Exposed Populations and 
Lifestages
    4.4. Exposure Characterization
5. Risk Characterization
    5.1. Purpose
    5.2. Application
    5.3. Presentation of the Risk Characterization Summary
    5.4. Content of the Risk Characterization Summary
Appendix: Major Default Options
Appendix B: EPA's Guidance for Data Quality Assessment
References

List of Figures

Figure 1-1. Flow chart for early-life risk assessment using mode of 
action framework
Figure 3-1. Compatibility of Alternative Points of Departure with 
Observed and Modeled Tumor Incidences
Figure 3-2. Crossing between 10% and 1% Dose-Response Curves for 
Bladder Carcinomas and Liver Carcinomas Induced by 2-AAF

1. Introduction

1.1. Purpose and Scope of the Guidelines

    These guidelines revise and replace the U.S. Environmental 
Protection Agency's (EPA's, or the Agency's) Guidelines for Carcinogen 
Risk Assessment, published in 51 FR 33992, September 24, 1986 (U.S. 
EPA, 1986a) and the 1999 interim final guidelines (U.S. EPA, 1999a; see 
U.S. EPA 2001b). They provide EPA staff with guidance for developing 
and using risk assessments. They also provide basic information to the 
public about the Agency's risk assessment methods.
    These cancer guidelines are used with other risk assessment 
guidelines, such as the Guidelines for Mutagenicity Risk Assessment 
(U.S. EPA, 1986b) and the Guidelines for Exposure Assessment (U.S. EPA, 
1992a). Consideration of other Agency guidance documents is also 
important in assessing cancer risks where procedures for evaluating 
specific target organ effects have been developed (e.g., assessment of 
thyroid follicular cell tumors, U.S. EPA, 1998a). All of EPA's 
guidelines should be consulted when conducting a risk assessment in 
order to ensure that information from studies on carcinogenesis and 
other health effects are considered together in the overall 
characterization of risk. This is particularly true in the case in 
which a precursor effect for a tumor is also a precursor or endpoint of 
other health effects or when there is a concern for a particular 
susceptible life-stage for which the Agency has developed guidance, for 
example, Guidelines for Developmental Toxicity Risk Assessment (U.S. 
EPA, 1991a). The developmental guidelines discuss hazards to children 
that may result from exposures during preconception and prenatal or 
postnatal development to

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sexual maturity. Similar guidelines exist for reproductive toxicant 
risk assessments (U.S. EPA, 1996a) and for neurotoxicity risk 
assessment (U.S. EPA, 1998b). The overall characterization of risk is 
conducted within the context of broader policies and guidance such as 
Executive Order 13045, ``Protection of Children From Environmental 
Health Risks and Safety Risks'' (Executive Order 13045, 1997) which is 
the primary directive to Federal agencies and departments to identify 
and assess environmental health risks and safety risks that may 
disproportionately affect children.
    The cancer guidelines encourage both consistency in the procedures 
that support scientific components of Agency decision making and 
flexibility to allow incorporation of innovations and contemporaneous 
scientific concepts. In balancing these goals, the Agency relies on 
established scientific peer review processes (U.S. EPA, 2000a; OMB 
2004). The cancer guidelines incorporate basic principles and science 
policies based on evaluation of the currently available information. 
The Agency intends to revise these cancer guidelines when substantial 
changes are necessary. As more information about carcinogenesis 
develops, the need may arise to make appropriate changes in risk 
assessment guidance. In the interim, the Agency intends to issue 
special reports, after appropriate peer review, to supplement and 
update guidance on single topics (e.g., U.S. EPA, 1991b). One such 
guidance document, Supplemental Guidance for Assessing Susceptibility 
from Early-Life Exposure to Carcinogens (``Supplemental Guidance''), 
was developed in conjunction with these cancer guidelines (U.S. EPA., 
2005). Because both the methodology and the data in the Supplemental 
Guidance (see Section 1.3.6) are expected to evolve more rapidly than 
the issues addressed in these cancer guidelines, the two were developed 
as separate documents. The Supplemental Guidance, however, as well as 
any other relevant (including subsequent) guidance documents, should be 
considered along with these cancer guidelines as risk assessments for 
carcinogens are generated. The use of supplemental guidance, such as 
the Supplemental Guidance for Assessing Cancer Susceptibility from 
Early-life Exposure to Carcinogens, has the advantage of allowing the 
Supplemental Guidance to be modified as more data become available. 
Thus, the consideration of new, peer-reviewed scientific understanding 
and data in an assessment can always be consistent with the purposes of 
these cancer guidelines.
    These cancer guidelines are intended as guidance only. They do not 
establish any substantive ``rules'' under the Administrative Procedure 
Act or any other law and have no binding effect on EPA or any regulated 
entity, but instead represent a non-binding statement of policy. EPA 
believes that the cancer guidelines represent a sound and up-to-date 
approach to cancer risk assessment, and the cancer guidelines enhance 
the application of the best available science in EPA's risk 
assessments. However, EPA cancer risk assessments may be conducted 
differently than envisioned in the cancer guidelines for many reasons, 
including (but not limited to) new information, new scientific 
understanding, or new science policy judgment. The science of risk 
assessment continues to develop rapidly, and specific components of the 
cancer guidelines may become outdated or may otherwise require 
modification in individual settings. Use of the cancer guidelines in 
future risk assessments will be based on decisions by EPA that the 
approaches are suitable and appropriate in the context of those 
particular risk assessments. These judgments will be tested through 
peer review, and risk assessments will be modified to use different 
approaches if appropriate.

1.2. Organization and Application of the Cancer Guidelines

1.2.1. Organization
    Publications by the Office of Science and Technology (OSTP, 1985) 
and the National Research Council (NRC) (NRC, 1983, 1994) provide 
information and general principles about risk assessment. Risk 
assessment uses available scientific information on the properties of 
an agent \1\ and its effects in biological systems to provide an 
evaluation of the potential for harm as a consequence of environmental 
exposure. The 1983 and 1994 NRC documents organize risk assessment 
information into four areas: Hazard identification, dose-response 
assessment, exposure assessment, and risk characterization. This 
structure appears in these cancer guidelines, with additional emphasis 
placed on characterization of evidence and conclusions in each area of 
the assessment. In particular, the cancer guidelines adopt the approach 
of the NRC's 1994 report in adding a dimension of characterization to 
the hazard identification step: an evaluation of the conditions under 
which its expression is anticipated. Risk assessment questions 
addressed in these cancer guidelines are as follows.
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    \1\ The term ``agent'' refers generally to any chemical 
substance, mixture, or physical or biological entity being assessed, 
unless otherwise noted (See Section 1.2.2 for a note on radiation.).
---------------------------------------------------------------------------

     For hazard--Can the identified agent present a 
carcinogenic hazard to humans and, if so, under what circumstances?
     For dose response--At what levels of exposure might 
effects occur?
     For exposure--What are the conditions of human exposure?
     For risk--What is the character of the risk? How well do 
data support conclusions about the nature and extent of the risk from 
various exposures?
    The risk characterization process first summarizes findings on 
hazard, dose response, and exposure characterizations and then develops 
an integrative analysis of the whole risk case. It ends in the writing 
of a technical risk characterization. Other documents, such as 
summaries for the risk managers and the public, reflecting the key 
points of the risk characterization are usually written. A summary for 
managers is a presentation for those who may or may not be familiar 
with the scientific details of cancer assessment. It also provides 
information for other interested readers. The initial steps in the risk 
characterization process are to make building blocks in the form of 
characterizations of the assessments of hazard, dose response, and 
exposure. The individual assessments and characterizations are then 
integrated to arrive at risk estimates for exposure scenarios of 
interest. As part of the characterization process, explicit evaluations 
are made of the hazard and risk potential for susceptible lifestages, 
including children (U.S. EPA, 1995, 2000b).
    The 1994 NRC document also explicitly called attention to the role 
of the risk assessment process in identifying scientific uncertainties 
that, if addressed, could serve to reduce their uncertainty in future 
iterations of the risk assessment. NRC recommended that when the Agency 
``reports estimates of risk to decisions-makers and the public, it 
should present not only point estimates of risk, but also the sources 
and magnitudes of uncertainty associated with these estimates'' (p. 
15). Thus, the identified uncertainties serve as a feedback loop to the 
research community and decisionmakers, specifying areas and types of 
information that would be particularly useful.
    There are several reasons for individually characterizing the 
hazard, dose response, and exposure

[[Page 17770]]

assessments. One is that they are often done by different people than 
those who do the integrative analyses. The second is that there is very 
often a lapse of time between the conduct of hazard and dose-response 
analyses and the conduct of exposure assessment and integrative 
analysis. Thus, it is important to capture characterizations of 
assessments as the assessments are done to avoid the need to go back 
and reconstruct them. Finally, frequently a single hazard assessment is 
used by several programs for several different exposure scenarios. 
There may be one or several documents involved. ``Integrative 
analysis'' is a generic term; and many documents that have other titles 
may contain integrative analyses. In the following sections, the 
elements of these characterizations are discussed.
1.2.2. Application
    The cancer guidelines apply within the framework of policies 
provided by applicable EPA statutes and do not alter such policies.
     The cancer guidelines cover the assessment of available 
data. They do not imply that one kind of data or another is 
prerequisite for regulatory action concerning any agent. It is 
important that, when evaluating and considering the use of any data, 
EPA analysts incorporate the basic standards of quality, as defined by 
the EPA Information Quality Guidelines (U.S. EPA, 2002a see Appendix B) 
and other Agency guidance on data quality such as the EPA Quality 
Manual for Environmental Programs (U.S. EPA, 2000e), as well as OMB 
Guidelines for Ensuring and Maximizing the Quality, Utility, and 
Integrity of Information Disseminated by Federal Agencies (OMB, 2002). 
It is very important that all analyses consider the basic standards of 
quality, including objectivity, utility, and integrity. A summary of 
the factors and considerations generally used by the Agency when 
evaluating and considering the use of scientific and technical 
information is contained in EPA's A Summary of General Assessment 
Factors for Evaluating the Quality of Scientific and Technical 
Information (U.S. EPA, 2003).
     Risk management applies directives in statutes, which may 
require consideration of potential risk or solely hazard or exposure 
potential, along with social, economic, technical, and other factors in 
decision making. Risk assessments may be used to support decisions, but 
in order to maintain their integrity as decision-making tools, they are 
not influenced by consideration of the social or economic consequences 
of regulatory action.
    The assessment of risk from radiation sources is informed by the 
continuing examination of human data by the National Academy of 
Sciences/NRC in its series of numbered reports: ``Biological Effects of 
Ionizing Radiation.'' Although some of the general principles of these 
cancer guidelines may also apply to radiation risk assessments, some of 
the details of their risk assessment procedures may not, as they are 
most focused on other kinds of agents. Therefore, these cancer 
guidelines are not intended to provide the primary source of, or 
guidance for, the Agency's evaluation of the carcinogenic risks of 
radiation.
    Not every EPA assessment has the same scope or depth, a factor 
recognized by the National Academy of Sciences (NRC, 1996). For 
example, EPA's Information Quality Guidelines (U.S. EPA, 2002a, see 
Appendix B) discuss influential information that ``will have or does 
have a clear and substantial impact * * * on important public policies 
or private sector decisions * * * that should adhere to a rigorous 
standard of quality.'' It is often difficult to know a priori how the 
results of a risk assessment are likely to be used by the Agency. Some 
risk assessments may be used by Agency economists and policy analysts, 
and the necessary information for such analyses, as discussed in detail 
later in this document, should be included when practicable (U.S. EPA, 
2002a). On the other hand, Agency staff often conduct screening-level 
assessments for priority setting or separate assessments of hazard or 
exposure for ranking purposes or to decide whether to invest resources 
in collecting data for a full assessment. Moreover, a given assessment 
of hazard and dose response may be used with more than one exposure 
assessment that may be conducted separately and at different times as 
the need arises in studying environmental problems related to various 
exposure media. The cancer guidelines apply to these various situations 
in appropriate detail, given the scope and depth of the particular 
assessment. For example, a screening assessment may be based almost 
entirely on structure-activity relationships (SARs) and default 
options, when other data are not readily available. When more data and 
resources are readily available, assessments can use a critical 
analysis of all of the available data as the starting point of the risk 
assessment. Under these conditions, default options would only be used 
to address uncertainties or the absence of critical data. Default 
options are inferences based on general scientific knowledge of the 
phenomena in question and are also matters of policy concerning the 
appropriate way to bridge uncertainties that concern potential risk to 
human health.
    These cancer guidelines do not suggest that all of the kinds of 
data covered here will need to be available or used for either 
assessment or decision making. The level of detail of an assessment is 
a matter of Agency management discretion regarding applicable decision-
making needs. The Agency generally presumes that key cancer information 
(e.g., assessments contained in the Agency's Integrated Risk 
Information System) is ``influential information'' as defined by the 
EPA Information Quality Guidelines and ``highly influential'' as 
defined by OMB's Information Quality Bulletin for Peer Review (OMB 
2004).

1.3. Key Features of the Cancer Guidelines

1.3.1. Critical Analysis of Available Information as the Starting Point 
for Evaluation
    As an increasing understanding of carcinogenesis is becoming 
available, these cancer guidelines adopt a view of default options that 
is consistent with EPA's mission to protect human health while adhering 
to the tenets of sound science. Rather than viewing default options as 
the starting point from which departures may be justified by new 
scientific information, these cancer guidelines view a critical 
analysis of all of the available information that is relevant to 
assessing the carcinogenic risk as the starting point from which a 
default option may be invoked if needed to address uncertainty or the 
absence of critical information. Preference is given to using 
information that has been peer reviewed, e.g., reported in peer-
reviewed scientific journals. The primary goal of EPA actions is 
protection of human health; accordingly, as an Agency policy, risk 
assessment procedures, including default options that are used in the 
absence of scientific data to the contrary, should be health protective 
(U.S. EPA, 1999b).
    Use of health protective risk assessment procedures as described in 
these cancer guidelines means that estimates, while uncertain, are more 
likely to overstate than understate hazard and/or risk. NRC (1994) 
reaffirmed the use of default options as ``a reasonable way to cope 
with uncertainty about the choice of appropriate models or theory'' (p. 
104). NRC saw the need to treat uncertainty in a predictable way that 
is

[[Page 17771]]

``scientifically defensible, consistent with the agency's statutory 
mission, and responsive to the needs of decision-makers'' (p. 86). The 
extent of health protection provided to the public ultimately depends 
upon what risk managers decide is the appropriate course of regulatory 
action. When risk assessments are performed using only one set of 
procedures, it may be difficult for risk managers to determine how much 
health protectiveness is built into a particular hazard determination 
or risk characterization. When there are alternative procedures having 
significant biological support, the Agency encourages assessments to be 
performed using these alternative procedures, if feasible, in order to 
shed light on the uncertainties in the assessment, recognizing that the 
Agency may decide to give greater weight to one set of procedures than 
another in a specific assessment or management decision.
    Encouraging risk assessors to be receptive to new scientific 
information, NRC discussed the need for departures from default options 
when a ``sufficient showing'' is made. It called on EPA to articulate 
clearly its criteria for a departure so that decisions to depart from 
default options would be ``scientifically credible and receive public 
acceptance'' (p. 91). It was concerned that ad hoc departures would 
undercut the scientific credibility of a risk assessment. NRC 
envisioned that principles for choosing and departing from default 
options would balance several objectives, including ``protecting the 
public health, ensuring scientific validity, minimizing serious errors 
in estimating risks, maximizing incentives for research, creating an 
orderly and predictable process, and fostering openness and 
trustworthiness'' (p. 81).
    Appendices N-1 and N-2 of NRC (1994) discussed two competing 
standards for choosing default options articulated by members of the 
committee. One suggested approach would evaluate a departure in terms 
of whether ``it is scientifically plausible'' and whether it ``tends to 
protect public health in the face of scientific uncertainty'' (p. 601). 
An alternative approach ``emphasizes scientific plausibility with 
regard to the use of alternative models'' (p. 631). Reaching no 
consensus on a single approach, NRC recognized that developing criteria 
for departures is an EPA policy matter.
    The basis for invoking a default option depends on the 
circumstances. Generally, if a gap in basic understanding exists or if 
agent-specific information is missing, a default option may be used. If 
agent-specific information is present but critical analysis reveals 
inadequacies, a default option may also be used. If critical analysis 
of agent-specific information is consistent with one or more 
biologically based models as well as with the default option, the 
alternative models and the default option are both carried through the 
assessment and characterized for the risk manager. In this case, the 
default model not only fits the data, but also serves as a benchmark 
for comparison with other analyses. This case also highlights the 
importance of extensive experimentation to support a conclusion about 
mode of action, including addressing the issue of whether alternative 
modes of action are also plausible. Section 2.4 provides a framework 
for critical analysis of mode of action information to address the 
extent to which the available information supports the hypothesized 
mode of action, whether alternative modes of action are also plausible, 
and whether there is confidence that the same inferences can be 
extended to populations and lifestages that are not represented among 
the experimental data.
    Generally, cancer risk decisions strive to be ``scientifically 
defensible, consistent with the agency's statutory mission, and 
responsive to the needs of decision-makers'' (NRC, 1994). Scientific 
defensibility would be evaluated through use of EPA's Science Advisory 
Board, EPA's Office of Pesticide Programs' Scientific Advisory Panel, 
or other independent expert peer review panels to determine whether a 
consensus among scientific experts exists. Consistency with the 
Agency's statutory mission would consider whether the risk assessment 
overall supports EPA's mission to protect human health and safeguard 
the natural environment. Responsiveness to the needs of decisionmakers 
would take into account pragmatic considerations such as the nature of 
the decision; the required depth of analysis; the utility, time, and 
cost of generating new scientific data; and the time, personnel, and 
resources allotted to the risk assessment.
    With a multitude of types of data, analyses, and risk assessments, 
as well as the diversity of needs of decisionmakers, it is neither 
possible nor desirable to specify step-by-step criteria for decisions 
to invoke a default option. A discussion of major default options 
appears in the Appendix. Screening-level assessments may more readily 
use default parameters, even worst-case assumptions, that would not be 
appropriate in a full-scale assessment. On the other hand, significant 
risk management decisions will often benefit from a more comprehensive 
assessment, including alternative risk models having significant 
biological support. To the extent practicable, such assessments should 
provide central estimates of potential risks in conjunction with lower 
and upper bounds (e.g., confidence limits) and a clear statement of the 
uncertainty associated with these estimates.
    In the absence of sufficient data or understanding to develop of a 
robust, biologically based model, an appropriate policy choice is to 
have a single preferred curve-fitting model for each type of data set. 
Many different curve-fitting models have been developed, and those that 
fit the observed data reasonably well may lead to several-fold 
differences in estimated risk at the lower end of the observed range. 
In addition, goodness-of-fit to the experimental observations is not by 
itself an effective means of discriminating among models that 
adequately fit the data (OSTP, 1985). To provide some measure of 
consistency across different carcinogen assessments, EPA uses a 
standard curve-fitting procedure for tumor incidence data. Assessments 
that include a different approach should provide an adequate 
justification and compare their results with those from the standard 
procedure. Application of models to data should be conducted in an open 
and transparent manner.
1.3.2. Mode of Action
    The use of mode of action \2\ in the assessment of potential 
carcinogens is a main focus of these cancer guidelines. This area of 
emphasis arose because of the significant scientific advances that have 
developed concerning the causes of cancer induction. Elucidation of a 
mode of action for a particular cancer response in animals or humans is 
a data-rich determination. Significant

[[Page 17772]]

information should be developed to ensure that a scientifically 
justifiable mode of action underlies the process leading to cancer at a 
given site. In the absence of sufficiently, scientifically justifiable 
mode of action information, EPA generally takes public health-
protective, default positions regarding the interpretation of 
toxicologic and epidemiologic data: Animal tumor findings are judged to 
be relevant to humans, and cancer risks are assumed to conform with low 
dose linearity.
---------------------------------------------------------------------------

    \2\ The term ``mode of action'' is defined as a sequence of key 
events and processes, starting with interaction of an agent with a 
cell, proceeding through operational and anatomical changes, and 
resulting in cancer formation. A ``key event'' is an empirically 
observable precursor step that is itself a necessary element of the 
mode of action or is a biologically based marker for such an 
element. Mode of action is contrasted with ``mechanism of action,'' 
which implies a more detailed understanding and description of 
events, often at the molecular level, than is meant by mode of 
action. The toxicokinetic processes that lead to formation or 
distribution of the active agent to the target tissue are considered 
in estimating dose but are not part of the mode of action as the 
term is used here. There are many examples of possible modes of 
carcinogenic action, such as mutagenicity, mitogenesis, inhibition 
of cell death, cytotoxicity with reparative cell proliferation, and 
immune suppression.
---------------------------------------------------------------------------

    Understanding of mode of action can be a key to identifying 
processes that may cause chemical exposures to differentially affect a 
particular population segment or lifestage. Some modes of action are 
anticipated to be mutagenic and are assessed with a linear approach. 
This is the mode of action of radiation and several other agents that 
are known carcinogens. Other modes of action may be modeled with either 
linear or nonlinear \3\ approaches after a rigorous analysis of 
available data under the guidance provided in the framework for mode of 
action analysis (see Section 2.4.3).
---------------------------------------------------------------------------

    \3\ The term ``nonlinear'' is used here in a narrower sense than 
its usual meaning in the field of mathematical modeling. In these 
cancer guidelines, the term ``nonlinear'' refers to threshold models 
(which show no response over a range of low doses that include zero) 
and some nonthreshold models (e.g., a quadractic model, which shows 
some response at all doses above zero). In these cancer guidelines, 
a nonlinear model is one whose slope is zero at (and perhaps above) 
a dose of zero. A low-dose-linear model is one whose slope is 
greater than zero at a dose of zero. A low-dose-linear model 
approximates a straight line only at very low doses; at higher doses 
near the observed data, a low-dose-linear model can display 
curvature. The term ``low-dose-linear'' is often abbreviated 
``linear,'' although a low-dose-linear model is not linear at all 
doses. Use of nonlinear approaches does not imply a biological 
threshold dose below which the response is zero. Estimating 
thresholds can be problematic; for example, a response that is not 
statistically significant can be consistent with a small risk that 
falls below an experiment's power of detection.
---------------------------------------------------------------------------

1.3.3. Weight of Evidence Narrative
    The cancer guidelines emphasize the importance of weighing all of 
the evidence in reaching conclusions about the human carcinogenic 
potential of agents. This is accomplished in a single integrative step 
after assessing all of the individual lines of evidence, which is in 
contrast to the step-wise approach in the 1986 cancer guidelines. 
Evidence considered includes tumor findings, or lack thereof, in humans 
and laboratory animals; an agent's chemical and physical properties; 
its structure-activity relationships (SARs) as compared with other 
carcinogenic agents; and studies addressing potential carcinogenic 
processes and mode(s) of action, either in vivo or in vitro. Data from 
epidemiologic studies are generally preferred for characterizing human 
cancer hazard and risk. However, all of the information discussed above 
could provide valuable insights into the possible mode(s) of action and 
likelihood of human cancer hazard and risk. The cancer guidelines 
recognize the growing sophistication of research methods, particularly 
in their ability to reveal the modes of action of carcinogenic agents 
at cellular and subcellular levels as well as toxicokinetic processes.
    Weighing of the evidence includes addressing not only the 
likelihood of human carcinogenic effects of the agent but also the 
conditions under which such effects may be expressed, to the extent 
that these are revealed in the toxicological and other biologically 
important features of the agent.
    The weight of evidence narrative to characterize hazard summarizes 
the results of the hazard assessment and provides a conclusion with 
regard to human carcinogenic potential. The narrative explains the 
kinds of evidence available and how they fit together in drawing 
conclusions, and it points out significant issues/strengths/limitations 
of the data and conclusions. Because the narrative also summarizes the 
mode of action information, it sets the stage for the discussion of the 
rationale underlying a recommended approach to dose-response 
assessment.
    In order to provide some measure of clarity and consistency in an 
otherwise free-form, narrative characterization, standard descriptors 
are used as part of the hazard narrative to express the conclusion 
regarding the weight of evidence for carcinogenic hazard potential. 
There are five recommended standard hazard descriptors: ``Carcinogenic 
to Humans,'' ``Likely to Be Carcinogenic to Humans,'' ``Suggestive 
Evidence of Carcinogenic Potential,'' ``Inadequate Information to 
Assess Carcinogenic Potential,'' and ``Not Likely to Be Carcinogenic to 
Humans.'' Each standard descriptor may be applicable to a wide variety 
of data sets and weights of evidence and is presented only in the 
context of a weight of evidence narrative. Furthermore, as described in 
Section 2.5 of these cancer guidelines, more than one conclusion may be 
reached for an agent.
1.3.4. Dose-Response Assessment
    Dose-response assessment evaluates potential risks to humans at 
particular exposure levels. The approach to dose-response assessment 
for a particular agent is based on the conclusion reached as to its 
potential mode(s) of action for each tumor type. Because an agent may 
induce multiple tumor types, the dose-response assessment includes an 
analysis of all tumor types, followed by an overall synthesis that 
includes a characterization of the risk estimates across tumor types, 
the strength of the mode of action information of each tumor type, and 
the anticipated relevance of each tumor type to humans, including 
susceptible populations and lifestages (e.g., childhood).
    Dose-response assessment for each tumor type is performed in two 
steps: assessment of observed data to derive a point of departure 
(POD),\4\ followed by extrapolation to lower exposures to the extent 
that is necessary. Data from epidemiologic studies, of sufficient 
quality, are generally preferred for estimating risks. When animal 
studies are the basis of the analysis, the estimation of a human-
equivalent dose should utilize toxicokinetic data to inform cross-
species dose scaling if appropriate and if adequate data are available. 
Otherwise, default procedures should be applied. For oral dose, based 
on current science, an appropriate default option is to scale daily 
applied doses experienced for a lifetime in proportion to body weight 
raised to the \3/4\ power (U.S. EPA, 1992b). For inhalation dose, based 
on current science, an appropriate default methodology estimates 
respiratory deposition of particles and gases and estimates internal 
doses of gases with different absorption characteristics. When 
toxicokinetic modeling (see Section 3.1.2) is used without 
toxicodynamic modeling (see Section 3.2.2), the dose-response 
assessment develops and supports an approach for addressing 
toxicodynamic equivalence, perhaps by retaining some of the cross-
species scaling factor (see Section 3.1.3). Guidance is also provided 
for adjustment of dose from adults to children (see Section 4.3.1).
---------------------------------------------------------------------------

    \4\ A ``point of departure'' (POD) marks the beginning of 
extrapolation to lower doses. The POD is an estimated dose (usually 
expressed in human-equivalent terms) near the lower end of the 
observed range, without significant extrapolation to lower doses.
---------------------------------------------------------------------------

    Response data on effects of the agent on carcinogenic processes are 
analyzed (nontumor data) in addition to data on tumor incidence. If 
appropriate, the analyses of data on tumor incidence and on precursor 
effects may be used in combination. To the extent the relationship 
between precursor effects and tumor incidence are known, precursor data 
may be used to estimate a dose-response function below the observable 
tumor data. Study of the dose-response function for effects

[[Page 17773]]

believed to be part of the carcinogenic process influenced by the agent 
may also assist in evaluating the relationship of exposure and response 
in the range of observation and at exposure levels below the range of 
observation.
    The first step of dose-response assessment is evaluation within the 
range of observation. Approaches to analysis of the range of 
observation of epidemiologic studies are determined by the type of 
study and how dose and response are measured in the study. In the 
absence of adequate human data for dose-response analysis, animal data 
are generally used. If there are sufficient quantitative data and 
adequate understanding of the carcinogenic process, a biologically 
based model may be developed to relate dose and response data on an 
agent-specific basis. Otherwise, as a default procedure, a standard 
model can be used to curve-fit the data.
    The POD for extrapolating the relationship to environmental 
exposure levels of interest, when the latter are outside the range of 
observed data, is generally the lower 95% confidence limit on the 
lowest dose level that can be supported for modeling by the data. SAB 
(1997) suggested that, ``it may be appropriate to emphasize lower 
statistical bounds in screening analyses and in activities designed to 
develop an appropriate human exposure value, since such activities 
require accounting for various types of uncertainties and a lower bound 
on the central estimate is a scientifically-based approach accounting 
for the uncertainty in the true value of the ED10 [or 
central estimate].'' However, the consensus of the SAB (1997) was that, 
``both point estimates and statistical bounds can be useful in 
different circumstances, and recommended that the Agency routinely 
calculate and present the point estimate of the ED10 [or 
central estimate] and the corresponding upper and lower 95% statistical 
bounds.'' For example, it may be appropriate to emphasize the central 
estimate in activities that involve formal uncertainty analysis that 
are required by OMB Circular A-4 (OMB, 2003) as well as ranking agents 
as to their carcinogenic hazard. Thus, risk assessors should calculate, 
to the extent practicable, and present the central estimate and the 
corresponding upper and lower statistical bounds (such as confidence 
limits) to inform decisionmakers.
    The second step of dose-response assessment is extrapolation to 
lower dose levels, if needed. This extrapolation is based on extension 
of a biologically based model if supported by substantial data (see 
Section 3.3.2). Otherwise, default approaches can be applied that are 
consistent with current understanding of mode(s) of action of the 
agent, including approaches that assume linearity or nonlinearity of 
the dose-response relationship, or both. A default approach for 
linearity extends a straight line from the POD to zero dose/zero 
response (see Section 3.3.3). The linear approach is used when: (1) 
There is an absence of sufficient information on modes of action or (2) 
the mode of action information indicates that the dose-response curve 
at low dose is or is expected to be linear. Where alternative 
approaches have significant biological support, and no scientific 
consensus favors a single approach, an assessment may present results 
using alternative approaches. A nonlinear approach can be used to 
develop a reference dose or a reference concentration (see Section 
3.3.4).
1.3.5. Susceptible Populations and Lifestages
    An important use of mode of action information is to identify 
susceptible populations and lifestages. It is rare to have 
epidemiologic studies or animal bioassays conducted in susceptible 
individuals. This information need can be filled by identifying the key 
events of the mode of action and then identifying risk factors, such as 
differences due to genetic polymorphisms, disease, altered organ 
function, lifestyle, and lifestage, that can augment these key events. 
To do this, the information about the key precursor events is reviewed 
to identify particular populations or lifestages that can be 
particularly susceptible to their occurrence (see Section 2.4.3.4). Any 
information suggesting quantitative differences between populations or 
lifestages is flagged for consideration in the dose-response assessment 
(see Section 3.5 and U.S. EPA 2002b).
1.3.6. Evaluating Risks From Childhood Exposures
    NRC (1994) recommended that ``EPA should assess risks to infants 
and children whenever it appears that their risks might be greater than 
those of adults.'' Executive Order 13045 (1997) requires that ``each 
Federal Agency shall make it a high priority to identify and assess 
environmental health and safety risks that may disproportionately 
affect children, and shall ensure that their policies, programs, and 
standards address disproportionate risks that result from environmental 
health risks or safety risks.'' In assessing risks to children, EPA 
considers both effects manifest during childhood and early-life 
exposures that can contribute to effects at any time later in life.
    These cancer guidelines view childhood as a sequence of lifestages 
rather than viewing children as a subpopulation, the distinction being 
that a subpopulation refers to a portion of the population, whereas a 
lifestage is inclusive of the entire population. Exposures that are of 
concern extend from conception through adolescence and also include 
pre-conception exposures of both parents. These cancer guidelines use 
the term ``childhood'' in this more inclusive sense.
    Rarely are there studies that directly evaluate risks following 
early-life exposure. Epidemiologic studies of early-life exposure to 
environmental agents are seldom available. Standard animal bioassays 
generally begin dosing after the animals are several weeks old, when 
many organ systems are mature. This could lead to an understatement of 
risk, because an accepted concept in the science of carcinogenesis is 
that young animals are usually more susceptible to the carcinogenic 
activity of a chemical than are mature animals (McConnell, 1992).
    At this time, there is some evidence of higher cancer risks 
following early-life exposure. For radiation carcinogenesis, data 
indicate that risks for several forms of cancer are highest following 
childhood exposure (NRC, 1990; Miller, 1995; U.S. EPA, 1999c). These 
human results are supported by the few animal bioassays that include 
perinatal (prenatal or early postnatal) exposure. Perinatal exposure to 
some agents can induce higher incidences of the tumors seen in standard 
bioassays; some examples include vinyl chloride (Maltoni et al., 1981), 
diethylnitrosamine (Peto et al., 1984), benzidine, DDT, dieldrin, and 
safrole (Vesselinovitch et al., 1979). Moreover, perinatal exposure to 
some agents, including vinyl chloride (Maltoni et al., 1981) and 
saccharin (Cohen, 1995; Whysner and Williams, 1996), can induce 
different tumors that are not seen in standard bioassays. Surveys 
comparing perinatal carcinogenesis bioassays with standard bioassays 
for a limited number of chemicals (McConnell, 1992; U.S. EPA, 1996b) 
have concluded that
     The same tumor sites are usually observed following either 
perinatal or adult exposure, and
     Perinatal exposure in conjunction with adult exposure 
usually increases the incidence of tumors or reduces the latent period 
before tumors are observed.
    The risk attributable to early-life exposure often appears modest 
compared with the risk from lifetime exposure, but it can be about 10-
fold

[[Page 17774]]

higher than the risk from an exposure of similar duration occurring 
later in life (Ginsberg, 2003). Further research is warranted to 
investigate the extent to which these findings apply to specific 
agents, chemical classes, and modes of action or in general.
    These empirical results are consistent with current understanding 
of the biological processes involved in carcinogenesis, which leads to 
a reasonable expectation that children can be more susceptible to many 
carcinogenic agents (Anderson et al., 2000; Birnbaum and Fenton, 2003; 
Ginsberg, 2003; Miller et al., 2002; Scheuplein et al., 2002). Some 
aspects potentially leading to childhood susceptibility are listed 
below.
     Differences in the capacity to metabolize and clear 
chemicals can result in larger or smaller internal doses of the active 
agent(s).
     More frequent cell division during development can result 
in enhanced expression of mutations due to the reduced time available 
for repair of DNA lesions (Slikker et al., 2004).
     Some embryonic cells, such as brain cells, lack key DNA 
repair enzymes.
     More frequent cell division during development can result 
in clonal expansion of cells with mutations from prior unrepaired DNA 
damage (Slikker et al., 2004).
     Some components of the immune system are not fully 
functional during development (Holladay and Smialowicz, 2000; Holsapple 
et al., 2003).
     Hormonal systems operate at different levels during 
different lifestages.
     Induction of developmental abnormalities can result in a 
predisposition to carcinogenic effects later in life (Anderson et al., 
2000; Birnbaum and Fenton, 2003; Fenton and Davis, 2002).
    To evaluate risks from early-life exposure, these cancer guidelines 
emphasize the role of toxicokinetic information to estimate levels of 
the active agent in children and toxicodynamic information to identify 
whether any key events of the mode of action are of increased concern 
early in life. Developmental toxicity studies can provide information 
on critical periods of exposure for particular targets of toxicity.
    An approach to assessing risks from early-life exposure is 
presented in Figure 1-1. In the hazard assessment, when there are mode 
of action data, the assessment considers whether these data have 
special relevance during childhood, considering the various aspects of 
development listed above. Examples of such data include toxicokinetics 
that predict a sufficiently large internal dose in children or a mode 
of action where a key precursor event is more likely to occur during 
childhood. There is no recommended default to settle the question of 
whether tumors arising through a mode of action are relevant during 
childhood; and adequate understanding the mode of action implies that 
there are sufficient data (on either the specific agent or the general 
mode of action) to form a confident conclusion about relevance during 
childhood (see Section 2.4.3.4).
    In the dose-response assessment, the potential for susceptibility 
during childhood warrants explicit consideration in each assessment. 
These cancer guidelines encourage developing separate risk estimates 
for children according to a tiered approach that considers what 
pertinent data are available (see Section 3.5). Childhood may be a 
susceptible period; moreover, exposures during childhood generally are 
not equivalent to exposures at other times and may be treated 
differently from exposures occurring later in life (see Section 3.5). 
In addition, adjustment of unit risk estimates may be warranted when 
used to estimate risks from childhood exposure (see Section 4.4).
    At this time, several limitations preclude a full assessment of 
children's risk. There are no generally used testing protocols to 
identify potential environmental causes of cancers that are unique to 
children, including several forms of childhood cancer and cancers that 
develop from parental exposures, and cases where developmental exposure 
may alter susceptibility to carcinogen exposure in the adult (Birnbaum 
and Fenton, 2003). Dose-response assessment is limited by an inability 
to observe how developmental exposure can modify incidence and latency 
and an inability to estimate the ultimate tumor response resulting from 
induced susceptibility to later carcinogen exposures.
    To partially address the limitations identified above, EPA 
developed in conjunction with these cancer guidelines, Supplemental 
Guidance for Assessing Susceptibility from Early-Life Exposure to 
Carcinogens (``Supplemental Guidance''). The Supplemental Guidance 
addresses a number of issues pertaining to cancer risks associated with 
early-life exposures generally, but provides specific guidance on 
procedures for adjusting cancer potency estimates only for carcinogens 
acting through a mutagenic mode of action. This Supplemental Guidance 
recommends, for such chemicals when no chemical-specific data exist, a 
default approach using estimates from chronic studies (i.e., cancer 
slope factors) with appropriate modifications to address the potential 
for differential risk of early-lifestage exposure.
    The Agency considered both the advantages and disadvantages to 
extending the recommended, age dependent adjustment factors for 
carcinogenic potency to carcinogenic agents for which the mode of 
action remains unknown. EPA decided to recommend these factors only for 
carcinogens acting through a mutagenic mode of action based on a 
combination of analysis of available data and long-standing science 
policy positions which govern the Agency's overall approach to 
carcinogen risk assessment. In general, the Agency prefers to rely on 
analyses of data, rather than general defaults. When data are available 
for a sensitive lifestage, they would be used directly to evaluate 
risks for that chemical and that lifestage on a case-by-case basis. In 
the case of nonmutagenic carcinogens, when the mode of action is 
unknown, the data were judged by EPA to be too limited and the modes of 
action too diverse to use this as a category for which a general 
default adjustment factor approach can be applied. In this situation, a 
linear low-dose extrapolation methodology (without further adjustment) 
is recommended. It is the Agency's long-standing science policy 
position that use of the linear low-dose extrapolation approach 
provides adequate public health conservatism in the absence of 
chemical-specific data indicating differential early-life sensitivity 
or when the mode of action is not mutagenic.
    The Agency expects to produce additional supplemental guidance for 
other modes of action, as data from new research and toxicity testing 
indicate it is warranted. EPA intends to focus its research, and work 
collaboratively with its federal partners, to improve understanding of 
the implications of early life exposure to carcinogens. Development of 
guidance for estrogenic agents and chemicals acting through other 
processes resulting in endocrine disruption and subsequent 
carcinogenesis, for example, might be a reasonable priority in light of 
the human experience with diethylstilbesterol and the existing early 
life animal studies. It is worth noting that each mode of action for 
endocrine disruption will probably require separate analysis.
    As the Agency examines additional carcinogenic agents, the age 
groupings may differ from those recommended for

[[Page 17775]]

assessing cancer risks from early-life exposure to chemicals with a 
mutagenic mode of action. Puberty and its associated biological 
changes, for example, involve many biological processes that could lead 
to changes in sensitivity to the effects of some carcinogens, depending 
on their mode of action. The Agency is interested in identifying 
lifestages that may be particularly sensitive or refractory for 
carcinogenesis, and believes that the mode of action framework 
described in these cancer guidelines is an appropriate mechanism for 
elucidating these lifestages. For each additional mode of action 
evaluated, the various age groupings determined to be at differential 
risk may differ from those proposed in the Supplemental Guidance. For 
example, the age groupings selected for the age-dependent adjustments 
for carcinogens acting through a mutagenic mode of action were 
initially selected based on the available data, i.e., for the 
laboratory animal age range representative of birth to < 2 years in 
humans. More limited data and information on human biology were used to 
determine a science-informed policy regarding 2 to < 16 years. Data 
were not available to refine the latter age group. If more data become 
available regarding carcinogens with a mutagenic mode of action, 
consideration may be given to further refinement of these age groups.
1.3.7. Emphasis on Characterization
    The cancer guidelines emphasize the importance of a clear and 
useful characterization narrative that summarizes the analyses of 
hazard, dose-response, and exposure assessment. These characterizations 
summarize the assessments to explain the extent and weight of evidence, 
major points of interpretation and rationale for their selection, 
strengths and weaknesses of the evidence and the analysis, and discuss 
alternative conclusions and uncertainties that deserve serious 
consideration (U.S. EPA, 2000b). They serve as starting materials for 
the overall risk characterization process that completes the risk 
assessment.
BILLING CODE 6560-50-P

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[GRAPHIC] [TIFF OMITTED] TN07AP05.000

BILLING CODE 6560-50-C

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2. Hazard Assessment

2.1. Overview of Hazard Assessment and Characterization

2.1.1. Analyses of Data
    The purpose of hazard assessment is to review and evaluate data 
pertinent to two questions: (1) Whether an agent may pose a 
carcinogenic hazard to human beings, and (2) under what circumstances 
an identified hazard may be expressed (NRC, 1994). Hazard assessment 
involves analyses of a variety of data that may range from observations 
of tumor responses to analysis of structure-activity relationships 
(SARs). The purpose of the assessment is not simply to assemble these 
separate evaluations; its purpose is to construct a total analysis 
examining what the biological data reveal as a whole about carcinogenic 
effects and mode of action of the agent, and their implications for 
human hazard and dose-response evaluation. Conclusions are drawn from 
weight-of-evidence evaluations based on the combined strength and 
coherence of inferences appropriately drawn from all of the available 
information. To the extent that data permit, hazard assessment 
addresses the question of mode of action of an agent as both an initial 
step in identifying human hazard potential and as a component in 
considering appropriate approaches to dose-response assessment.
    The topics in this chapter include analysis of tumor data, both 
human and animal, and analysis of other key information about 
properties and effects that relate to carcinogenic potential. The 
chapter addresses how information can be used to evaluate potential 
modes of action. It also provides guidance on performing a weight of 
evidence evaluation.
2.1.2. Presentation of Results
    Presentation of the results of hazard assessment should be informed 
by Agency guidance as discussed in Section 2.6. The results are 
presented in a technical hazard characterization that serves as a 
support to later risk characterization. It includes:
     A summary of the evaluations of hazard data,
     The rationales for its conclusions, and
     An explanation of the significant strengths or limitations 
of the conclusions.
    Another presentation feature is the use of a weight of evidence 
narrative that includes both a conclusion about the weight of evidence 
of carcinogenic potential and a summary of the data on which the 
conclusion rests. This narrative is a brief summary that in toto 
replaces the alphanumerical classification system used in EPA's 1986 
cancer guidelines (U.S. EPA, 1986a).

2.2. Analysis of Tumor Data

    Evidence of carcinogenicity comes from finding tumor increases in 
humans or laboratory animals exposed to a given agent or from finding 
tumors following exposure to structural analogues to the compound under 
review. The significance of observed or anticipated tumor effects is 
evaluated in reference to all the other key data on the agent. This 
section contains guidance for analyzing human and animal studies to 
decide whether there is an association between exposure to an agent or 
a structural analogue and occurrence of tumors. Note that the use of 
the term ``tumor'' in these cancer guidelines is defined as malignant 
neoplasms or a combination of malignant and corresponding benign 
neoplasms.
    Observation of only benign neoplasia may or may not have 
significance for evaluation under these cancer guidelines. Benign 
tumors that are not observed to progress to malignancy are assessed on 
a case-by-case basis. There is a range of possibilities for their 
overall significance. They may deserve attention because they are 
serious health problems even though they are not malignant; for 
instance, benign tumors may be a health risk because of their effect on 
the function of a target tissue such as the brain. They may be 
significant indicators of the need for further testing of an agent if 
they are observed in a short-term test protocol, or such an observation 
may add to the overall weight of evidence if the same agent causes 
malignancies in a long-term study. Knowledge of the mode of action 
associated with a benign tumor response may aid in the interpretation 
of other tumor responses associated with the same agent. In other 
cases, observation of a benign tumor response alone may have no 
significant health hazard implications when other sources of evidence 
show no suggestion of carcinogenicity.
2.2.1. Human Data
    Human data may come from epidemiologic studies or case reports. 
(Clinical human studies, which involve intentional exposures to 
substances, may provide toxicokinetic data, but generally not data on 
carcinogenicity.) The most common sources of human data for cancer risk 
assessment are epidemiologic investigations. Epidemiology is the study 
of the distribution of disease in human populations and the factors 
that may influence that distribution. The goals of cancer epidemiology 
are to identify distribution of cancer risk and determine the extent to 
which the risk can be attributed causally to specific exposures to 
exogenous or endogenous factors (see Centers for Disease Control and 
Prevention [CDC, 2004]). Epidemiologic data are extremely valuable in 
risk assessment because they provide direct evidence on whether a 
substance is likely to produce cancer in humans, thereby avoiding 
issues such as: species-to-species inference, extrapolation to 
exposures relevant to people, effects of concomitant exposures due to 
lifestyles. Thus, epidemiologic studies typically evaluate agents under 
more relevant conditions. When human data of high quality and adequate 
statistical power are available, they are generally preferable over 
animal data and should be given greater weight in hazard 
characterization and dose-response assessment, although both can be 
used.
    Null results from epidemiologic studies alone generally do not 
prove the absence of carcinogenic effects because such results can 
arise either from an agent being truly not carcinogenic or from other 
factors such as: inadequate statistical power, inadequate study design, 
imprecise estimates, or confounding factors. Moreover, null results 
from a well-designed and well-conducted epidemiologic study that 
contains usable exposure data can help to define upper limits for the 
estimated dose of concern for human exposure in cases where the overall 
weight of the evidence indicates that the agent is potentially 
carcinogenic in humans. Furthermore, data from a well designed and well 
conducted epidemiologic study that does not show positive results, in 
conjunction with compelling mechanistic information, can lend support 
to a conclusion that animal responses may not be predictive of a human 
cancer hazard.
    Epidemiology can also complement experimental evidence in 
corroborating or clarifying the carcinogenic potential of the agent in 
question. For example, epidemiologic studies that show elevated cancer 
risk for tumor sites corresponding to those at which laboratory animals 
experience increased tumor incidence can strengthen the weight of 
evidence of human carcinogenicity. Furthermore, biochemical or 
molecular epidemiology may help improve understanding of the mechanisms 
of human carcinogenesis.

[[Page 17778]]

2.2.1.1. Assessment of Evidence of Carcinogenicity From Human Data
    All studies that are considered to be of acceptable quality, 
whether yielding positive or null results, or even suggesting 
protective carcinogenic effects, should be considered in assessing the 
totality of the human evidence. Conclusions about the overall evidence 
for carcinogenicity from available studies in humans should be 
summarized along with a discussion of uncertainties and gaps in 
knowledge. Conclusions regarding the strength of the evidence for 
positive or negative associations observed, as well as evidence 
supporting judgments of causality, should be clearly described. In 
assessing the human data within the overall weight of evidence, 
determination about the strength of the epidemiologic evidence should 
clearly identify the degree to which the observed associations may be 
explained by other factors, including bias or confounding.
    Characteristics that are generally desirable in epidemiologic 
studies include (1) Clear articulation of study objectives or 
hypothesis; (2) proper selection and characterization of comparison 
groups (exposed and unexposed groups or case and control groups); (3) 
adequate characterization of exposure; (4) sufficient length of follow-
up for disease occurrence; (5) valid ascertainment of the causes of 
cancer morbidity and mortality; (6) proper consideration of bias and 
confounding factors; (7) adequate sample size to detect an effect; (8) 
clear, well-documented, and appropriate methodology for data collection 
and analysis; (9) adequate response rate and methodology for handling 
missing data; and (10) complete and clear documentation of results. No 
single criterion determines the overall adequacy of a study. Practical 
and resource constraints may limit the ability to address all of these 
characteristics in a study. The risk assessor is encouraged to consider 
how the limitations of the available studies might influence the 
conclusions. While positive biases may be due, for example, to a 
healthy worker effect, it is also important to consider negative 
biases, for example, workers who may leave the workforce due to illness 
caused either by high exposures to the agent or to effects of 
confounders such as smoking. The following discussions highlight the 
major factors included in an analysis of epidemiologic studies.
2.2.1.2. Types of Studies
    The major types of cancer epidemiologic study designs used for 
examining environmental causes of cancer are analytical studies and 
descriptive studies. Each study type has well-known strengths and 
weaknesses that affect interpretation of results, as summarized below 
(Lilienfeld and Lilienfeld, 1979; Mausner and Kramer, 1985; Kelsey et 
al., 1996; Rothman and Greenland, 1998).
    Analytical epidemiologic studies, which include case-control and 
cohort designs, are generally relied on for identifying a causal 
association between human exposure and adverse health effects. In case-
control studies, groups of individuals with (cases) and without 
(controls) a particular disease are identified and compared to 
determine differences in exposure. In cohort studies, a group of 
``exposed'' and ``nonexposed'' individuals are identified and studied 
over time to determine differences in disease occurrence. Cohort 
studies can be performed either prospectively or retrospectively from 
historical records. The type of study chosen may depend on the 
hypothesis to be evaluated. For example, case-control studies may be 
more appropriate for rare cancers while cohort studies may be more 
appropriate for more commonly occurring cancers.
    On the other hand, descriptive epidemiologic studies examine 
symptom or disease rates among populations in relation to personal 
characteristics such as age, gender, race, and temporal or 
environmental conditions. Descriptive studies are most frequently used 
to generate hypotheses about exposure factors, but subsequent 
analytical designs are necessary to infer causality. For example, 
cross-sectional designs might be used to compare the prevalence of 
cancer between areas near and far from a Superfund site. However, in 
studies where exposure and disease information applies only to the 
current conditions, it is not possible to infer that the exposure 
actually caused the disease. Therefore, these studies are used to 
identify patterns or trends in disease occurrence over time or in 
different geographical locations, but typical limitations in the 
characterization of populations in these studies make it difficult to 
infer the causal agent or degree of exposure.
    Case reports describe a particular effect in an individual or group 
of individuals who were exposed to a substance. These reports are often 
anecdotal or highly selective in nature and generally are of limited 
use for hazard assessment. Specifically, cancer causality can rarely be 
inferred from case reports alone. Investigative follow-up may or may 
not accompany such reports. For cancer, the most common types of case 
series are associated with occupational and childhood exposures. Case 
reports can be particularly valuable for identifying unique features, 
such as an association with an uncommon tumor (e.g., inhalation of 
vinyl chloride and hepatic angiosarcoma in workers or ingestion of 
diethylstilbestrol by mothers and clear-cell carcinoma of the vagina in 
offspring).
2.2.1.3. Exposure Issues
    For epidemiologic data to be useful in determining whether there is 
an association between health effects and exposure to an agent, there 
should be adequate characterization of exposure information. In 
general, greater weight should be given to studies with more precise 
and specific exposure estimates.
    Questions to address about exposure are: What can one reliably 
conclude about the exposure parameters including (but not limited to) 
the level, duration, route, and frequency of exposure of individuals in 
one population as compared with another? How sensitive are study 
results to uncertainties in these parameters?
    Actual exposure measurements are not available for many 
retrospective studies. Therefore, surrogates are often used to 
reconstruct exposure parameters. These may involve attributing 
exposures to job classifications in a workplace or to broader 
occupational or geographic groupings. Use of surrogates carries a 
potential for misclassification, i.e., individuals may be placed in an 
incorrect exposure group. Misclassification generally leads to reduced 
ability of a study to detect differences between study and referent 
populations.
    When either current or historical monitoring data are available, 
the exposure evaluation includes consideration of the error bounds of 
the monitoring and analytic methods and whether the data are from 
routine or accidental exposures. The potential for misclassification 
and for measurement errors is amenable to both qualitative and 
quantitative analysis. These are essential analyses for judging a 
study's results, because exposure estimation is the most critical part 
of a retrospective study.
2.2.1.4. Biological Markers
    Biological markers potentially offer excellent measures of exposure 
(Hulka and Margolin, 1992; Peto and Darby, 1994). In some cases, 
molecular or

[[Page 17779]]

cellular effects (e.g., DNA or protein adducts, mutation, chromosomal 
aberrations, levels of thyroid-stimulating hormone) can be measured in 
blood, body fluids, cells, and tissues to serve as biomarkers of 
exposure in humans and animals (Callemen et al., 1978; Birner et al., 
1990). As such, they can act as an internal surrogate measure of 
chemical dose, representing, as appropriate, either recent exposure 
(e.g., serum concentration) or accumulated exposure over some period 
(e.g., hemoglobin adducts). Validated markers of exposure such as 
alkylated hemoglobin from exposure to ethylene oxide (Van Sittert et 
al., 1985) or urinary arsenic (Enterline et al., 1987) can improve 
estimates of dose over the relevant time periods for the markers. 
Markers closely identified with effects promise to greatly increase the 
ability of studies to distinguish real effects from bias at low levels 
of relative risk between populations (Taylor et al., 1994; Biggs et 
al., 1993) and to resolve problems of confounding risk factors. 
However, when using molecular or cellular effects as biomarkers of 
exposure, since many of these changes are often not specific to just 
one type of exposure, it is important to be aware that changes may be 
due to exposures unrelated to the exposure of interest and attention 
must be paid to controlling for potential confounders.
    Biochemical or molecular epidemiologic studies may use biological 
markers of effect as indicators of disease or its precursors. The 
application of techniques for measuring cellular and molecular 
alterations due to exposure to specific environmental agents may allow 
conclusions to be drawn about the mechanisms of carcinogenesis (see 
section 2.4 for more information on this topic).
2.2.1.5. Confounding Factors
    Control for potential confounding factors is an important 
consideration in the evaluation of the design and in the analysis of 
observational epidemiologic studies. A confounder is a variable that is 
related to both the health outcome of concern (cancer) and exposure. 
Common examples include age, socioeconomic status, smoking habits, and 
diet. For instance, if older people are more likely to be exposed to a 
given contaminant as well as more likely to have cancer because of 
their age, age is considered a confounder. Adjustment for potentially 
confounding factors (from a statistical as contrasted with an 
epidemiologic point of view) can occur either in the design of the 
study (e.g., individual or group matching on critical factors) or in 
the statistical analysis of the results (stratification or direct or 
indirect adjustment). Direct adjustment in the statistical analysis may 
not be possible owing to the presentation of the data or because needed 
information was not collected during the study. In this case, indirect 
comparisons may be possible. For example, in the absence of data on 
smoking status among individuals in the study population, an 
examination of the possible contribution of cigarette smoking to 
increased lung cancer risk may be based on information from other 
sources, such as the American Cancer Society's longitudinal studies 
(Hammand, 1966; Garfinkel and Silverberg, 1991). The effectiveness of 
adjustments contributes to the ability to draw inferences from a study.
    Different studies involving exposure to an agent may have different 
confounding factors. If consistent increases in cancer risk are 
observed across a collection of studies with different confounding 
factors, the inference that the agent under investigation was the 
etiologic factor is strengthened.
    There may also be instances where the agent of interest is a risk 
factor in conjunction with another agent. For instance, interaction as 
well as effect-measure modification are sometimes construed to be 
confounding, but they are different than confounding. Interaction is 
described as a situation in which two or more risk factors modify the 
effect of each other with regard to the occurrence of a given effect. 
This phenomenon is sometimes described as effect-measure modification 
or heterogeneity of effect (Szklo and Nieto, 2000). Effect-measure 
modification refers to variation in the magnitude of measure exposure 
effect across levels of another variable (Rothman and Greenland, 1998). 
The variable across which the effect measure varies and is called an 
effect modifier (e.g., hepatitis virus B and aflatoxin in hepatic 
cancer). Interaction, on the other hand, means effect of the exposure 
on the outcome differs, depending on the presence of another variable 
(the effect modifier). When the effect of the exposure of interest is 
accentuated by another variable, it is said to be synergistic 
interaction. Synergistic interaction can be additive (e.g., hepatitis 
virus B and aflatoxin in hepatic cancer) or multiplicative (e.g., 
asbestos and smoking in lung cancer). If the effect of exposure is 
diminished or eliminated by another variable, it said to be 
antagonistic interaction (e.g., intake of vitamin E and lower 
occurrence of lung cancer).
2.2.1.6. Statistical Considerations
    The analysis should apply appropriate statistical methods to 
ascertain whether the observed association between exposure and effects 
would be expected by chance. A description of the method or methods 
used should include the reasons for their selection. Statistical 
analyses of the bias, confounding, and interaction are part of 
addressing the significance of an association and the power of a study 
to detect an effect.
    The analysis augments examination of the results for the whole 
population with exploration of the results for groups with 
comparatively greater exposure or time since first exposure. This may 
support identifying an association or establishing a dose-response 
trend. When studies show no association, such exploration may apply to 
determining an upper limit on potential human risk for consideration 
alongside results of animal tumor effects studies.
2.2.1.6.1. Likelihood of Observing an Effect
    The power of a study--the likelihood of observing an effect if one 
exists--increases with sample size, i.e., the number of subjects 
studied from a population. (For example, a quadrupling of a background 
rate in the 1 per 10,000 range would require more subjects who have 
experienced greater or longer exposure or lengthier follow-up, than a 
doubling of a background rate in the 1 per 100 range.) If the size of 
the effect is expected to be very small at low doses, higher doses or 
longer durations of exposure may be needed to have an appreciable 
likelihood of observing an effect with a given sample size. Because of 
the often long latency period in cancer development, the likelihood of 
observing an effect also depends on whether adequate time has elapsed 
since exposure began for effects to occur. Since the design of the 
study and the choice of analysis, as well as the design level of 
certainty in the results and the magnitude of response in an unexposed 
population also affect the likelihood of observing an effect, it is 
important to carefully interpret the absence of an observed effect. A 
unique feature that can be ascribed to the effects of a particular 
agent (such as a tumor type that is seen only rarely in the absence of 
the agent) can increase sensitivity by permitting separation of bias 
and confounding factors from real effects. Similarly, a biomarker 
particular to the agent can permit these distinctions. Statistical re-
analyses of data, particularly an examination of

[[Page 17780]]

different exposure indices, can give insight into potential exposure-
response relationships. These are all factors to explore in statistical 
analysis of the data.
2.2.1.6.2. Sampling and Other Bias Issues
    When comparing cases and controls or exposed and non-exposed 
populations, it would be preferable for the two populations to differ 
only in exposure to the agent in question. Because this is seldom the 
case, it is important to identify sources of sampling and other 
potential biases inherent in a study design or data collection methods.
    Bias is a systematic error. In epidemiologic studies, bias can 
occur in the selection of cases and controls or exposed and non-exposed 
populations, as well as the follow up of the groups, or the 
classification of disease or exposure. The size of the risks observed 
can be affected by noncomparability between populations of factors such 
as general health, diet, lifestyle, or geographic location; differences 
in the way case and control individuals recall past events; differences 
in data collection that result in unequal ascertainment of health 
effects in the populations; and unequal follow-up of individuals 
(Rothman and Greenland, 1998). Other factors worth consideration can be 
inherent in the available cohorts, e.g., use of occupational studies 
(the healthy worker effect), absence of one sex, or limitations in 
sample size for one or more ethnicities.
    The mere presence of biases does not invalidate a study, but should 
be reflected in the judgment of its strengths or weaknesses. Acceptance 
of studies for assessment depends on identifying their sources of bias 
and the possible effects on study results.
2.2.1.6.3. Combining Statistical Evidence Across Studies
    Meta-analysis is a means of integrating the results of multiple 
studies of similar health effects and risk factors. This technique is 
particularly useful when various studies yield varying degrees of risk 
or even conflicting associations (negative and positive). It is 
intended to introduce consistency and comprehensiveness into what 
otherwise might be a more subjective review of the literature. The 
value of such an analysis is dependent upon a systematic review of the 
literature that uses transparent criteria of inclusion and exclusion. 
In interpreting such analyses, it is important to consider the effects 
of differences in study quality, as well as the effect of publication 
bias. Meta-analysis may not be advantageous in some circumstances. 
These include when the relationship between exposure and disease is 
obvious from the individual studies; when there are only a few studies 
of the key health outcomes; when there is insufficient information from 
available studies related to disease, risk estimate, or exposure 
classification to insure comparability; or when there are substantial 
confounding or other biases that cannot be adjusted for in the analysis 
(Blair et al., 1995; Greenland, 1987; Peto, 1992).
2.2.1.7. Evidence for Causality
    Determining whether an observed association (risk) is causal rather 
than spurious involves consideration of a number of factors. Sir 
Bradford Hill (Hill, 1965) developed a set of guidelines for evaluating 
epidemiologic associations that can be used in conjunction with the 
discussion of causality such as the 2004 Surgeon General's report on 
smoking (CDC, 2004) and in other documents (e.g., Rothman and Greenland 
1998; IPCS, 1999). The critical assessment of epidemiologic evidence is 
conceptually based upon consideration of salient aspects of the 
evidence of associations so as to reach fundamental judgments as to the 
likely causal significance of the observed associations. In so doing, 
it is appropriate to draw from those aspects initially presented in 
Hill's classic monograph (Hill, 1965) and widely used by the scientific 
community in conducting such evidence-based reviews. A number of these 
aspects are judged to be particularly salient in evaluating the body of 
evidence available in this review, including the aspects described by 
Hill as strength, experiment, consistency, plausibility, and coherence. 
Other aspects identified by Hill, including temporality and biological 
gradient, are also relevant and considered here (e.g., in 
characterizing lag structures and concentration-response 
relationships), but are more directly addressed in the design and 
analyses of the individual epidemiologic studies included in this 
assessment. As discussed below, these salient aspects are interrelated 
and considered throughout the evaluation of the epidemiologic evidence 
generally reflected in the integrative synthesis of the mode of action 
framework.
    The general evaluation of the strength of the epidemiological 
evidence reflects consideration not only of the magnitude of reported 
effects estimates and their statistical significance, but also of the 
precision of the effects estimates and the robustness of the effects 
associations. Consideration of the robustness of the associations takes 
into account a number of factors, including in particular the impact of 
alternative models and model specifications and potential confounding 
factors, as well issues related to the consequences of measurement 
error. Consideration of the consistency of the effects associations 
involves looking across the results of studies conducted by different 
investigators in different places and times. Particular weight may be 
given, consistent with Hill's views, to the presence of ``similar 
results reached in quite different ways, e.g., prospectively and 
retrospectively'' (Hill, 1965). Looking beyond the epidemiological 
evidence, evaluation of the biological plausibility of the associations 
observed in epidemiologic studies reflects consideration of both 
exposure-related factors and toxicological evidence relevant to 
identification of potential modes of action (MOAs). Similarly, 
consideration of the coherence of health effects associations reported 
in the epidemiologic literature reflects broad consideration of 
information pertaining to the nature of the biological markers 
evaluated in toxicologic and epidemiologic studies.
    In identifying these aspects as being particularly salient in this 
assessment, it is also important to recognize that no one aspect is 
either necessary or sufficient for drawing inferences of causality. As 
Hill (1965) emphasized:

    None of my nine viewpoints can bring indisputable evidence for 
or against the cause-and-effect hypothesis and none can be required 
as a sine qua non. What they can do, with greater or less strength, 
is to help us to make up our minds on the fundamental question--is 
there any other way of explaining the set of facts before us, is 
there any other answer equally, or more, likely than cause and 
effect?

While these aspects frame considerations weighed in assessing the 
epidemiologic evidence, they do not lend themselves to being considered 
in terms of simple formulas or hard-and-fast rules of evidence leading 
to answers about causality (Hill, 1965). One, for example, cannot 
simply count up the numbers of studies reporting statistically 
significant results or statistically non-significant results for 
carcinogenesis and related MOAs and reach credible conclusions about 
the relative strength of the evidence and the likelihood of causality. 
Rather, these important considerations are taken into account 
throughout the assessment with a goal of producing an objective 
appraisal of the evidence (informed by peer and public comment and 
advice),

[[Page 17781]]

which includes the weighing of alternative views on controversial 
issues. Thus, although these guidelines have become known as ``causal 
criteria,'' it is important to note that they cannot be used as a 
strictly quantitative checklist. Rather, these ``criteria'' should be 
used to determine the strength of the evidence for concluding 
causality. In particular, the absence of one or more of the 
``criteria'' does not automatically exclude a study from consideration 
(e.g., see discussion in CDC, 2004). The list below has been adapted 
from Hill's guidelines as an aid in judging causality.
    (a) Consistency of the observed association. An inference of 
causality is strengthened when a pattern of elevated risks is observed 
across several independent studies. The reproducibility of findings 
constitutes one of the strongest arguments for causality. If there are 
discordant results among investigations, possible reasons such as 
differences in exposure, confounding factors, and the power of the 
study are considered.
    (b) Strength of the observed association. The finding of large, 
precise risks increases confidence that the association is not likely 
due to chance, bias, or other factors. A modest risk, however, does not 
preclude a causal association and may reflect a lower level of 
exposure, an agent of lower potency, or a common disease with a high 
background level.
    (c) Specificity of the observed association. As originally 
intended, this refers to increased inference of causality if one cause 
is associated with a single effect or disease (Hill, 1965). Based on 
our current understanding that many agents cause cancer at multiple 
sites, and many cancers have multiple causes, this is now considered 
one of the weaker guidelines for causality. Thus, although the presence 
of specificity may support causality, its absence does not exclude it.
    (d) Temporal relationship of the observed association. A causal 
interpretation is strengthened when exposure is known to precede 
development of the disease. Because a latent period of up to 20 years 
or longer is often associated with cancer development in adults, the 
study should consider whether exposures occurred sufficiently long ago 
to produce an effect at the time the cancer is assessed. This is among 
the strongest criteria for an inference of causality.
    (e) Biological gradient (exposure-response relationship). A clear 
exposure-response relationship (e.g., increasing effects associated 
with greater exposure) strongly suggests cause and effect, especially 
when such relationships are also observed for duration of exposure 
(e.g., increasing effects observed following longer exposure times). 
There are many possible reasons that an epidemiologic study may fail to 
detect an exposure-response relationship. For example, an analysis that 
included decreasing exposures due to improved technology that is 
combined with higher prior exposure in an initial analysis can require 
a segmented analysis to apportion exposure. Other reasons for failure 
to detect a relationship may include a small range of exposures. Thus, 
the absence of an exposure-response relationship does not exclude a 
causal relationship.
    (f) Biological plausibility. An inference of causality tends to be 
strengthened by consistency with data from experimental studies or 
other sources demonstrating plausible biological mechanisms. A lack of 
mechanistic data, however, is not a reason to reject causality.
    (g) Coherence. An inference of causality may be strengthened by 
other lines of evidence that support a cause-and-effect interpretation 
of the association. Information is considered from animal bioassays, 
toxicokinetic studies, and short-term studies. The absence of other 
lines of evidence, however, is not a reason to reject causality.
    (h) Experimental evidence (from human populations). Experimental 
evidence is seldom available from human populations and exists only 
when conditions of human exposure have occurred to create a ``natural 
experiment'' at different levels of exposure. Strong evidence for 
causality can be provided when a change in exposure brings about a 
change in disease frequency, for example, the decrease in the risk of 
lung cancer that follows cessation of smoking.
    (i) Analogy. SARs and information on the agent's structural 
analogues can provide insight into whether an association is causal. 
Similarly, information on mode of action for a chemical, as one of many 
structural analogues, can inform decisions regarding likely causality.
2.2.2. Animal Data
    Various whole-animal test systems are currently used or are under 
development for evaluating potential carcinogenicity. Cancer studies 
involving chronic exposure for most of the lifespan of an animal are 
generally accepted for evaluation of tumor effects (Tomatis et al., 
1989; Rall, 1991; Allen et al., 1988; but see Ames and Gold, 1990). 
Other studies of special design are useful for observing formation of 
preneoplastic lesions or tumors or investigating specific modes of 
action. Their applicability is determined on a case-by-case basis.
2.2.2.1. Long-Term Carcinogenicity Studies
    The objective of long-term carcinogenesis bioassays is to determine 
the potential carcinogenic hazard and dose-response relationships of 
the test agent. Carcinogenicity rodent studies are designed to examine 
the production of tumors as well as preneoplastic lesions and other 
indications of chronic toxicity that may provide evidence of treatment-
related effects and insights into the way the test agent produces 
tumors. Current standardized carcinogenicity studies in rodents test at 
least 50 animals per sex per dose group in each of three treatment 
groups and in a concurrent control group, usually for 18 to 24 months, 
depending on the rodent species tested (OECD, 1981; U.S. EPA, 1998c). 
The high dose in long-term studies is generally selected to provide the 
maximum ability to detect treatment-related carcinogenic effects while 
not compromising the outcome of the study through excessive toxicity or 
inducing inappropriate toxicokinetics (e.g., overwhelming absorption or 
detoxification mechanisms). The purpose of two or more lower doses is 
to provide some information on the shape of the dose-response curve. 
Similar protocols have been and continue to be used by many 
laboratories worldwide.
    All available studies of tumor effects in whole animals should be 
considered, at least preliminarily. The analysis should discard studies 
judged to be wholly inadequate in protocol, conduct, or results. 
Criteria for the technical adequacy of animal carcinogenicity studies 
have been published and should be used as guidance to judge the 
acceptability of individual studies (e.g., NTP, 1984; OSTP, 1985; 
Chhabra et al., 1990). As these criteria, in whole or in part, may be 
updated by the National Toxicology Program (NTP) and others, the 
analyst should consult the appropriate sources to determine both the 
current standards as well as those that were contemporaneous with the 
study. Care should be taken to include studies that provide some 
evidence bearing on carcinogenicity or that help interpret effects 
noted in other studies, even if these studies have some limitations of 
protocol or conduct. Such limited, but not wholly inadequate, studies 
can contribute as their deficiencies permit. The findings of

[[Page 17782]]

long-term rodent bioassays should be interpreted in conjunction with 
results of prechronic studies along with toxicokinetic studies and 
other pertinent information, if available. Evaluation of tumor effects 
takes into consideration both biological and statistical significance 
of the findings (Haseman, 1984, 1985, 1990, 1995). The following 
sections highlight the major issues in the evaluation of long-term 
carcinogenicity studies.
2.2.2.1.1. Dosing Issues
    Among the many criteria for technical adequacy of animal 
carcinogenicity studies is the appropriateness of dose selection. The 
selection of doses for chronic bioassays is based on scientific 
judgments and sound toxicologic principles. Dose selection should be 
made on the basis of relevant toxicologic information from prechronic, 
mechanistic, and toxicokinetic and mechanistic studies. A scientific 
rationale for dose selection should be clearly articulated (e.g., NTP, 
1984; ILSI, 1997). How well the dose selection is made is evaluated 
after the completion of the bioassay.
    Interpretation of carcinogenicity study results is profoundly 
affected by study exposure conditions, especially by inappropriate dose 
selection. This is particularly important in studies that do not show 
positive results for carcinogenicity, because failure to use a 
sufficiently high dose reduces the sensitivity of the studies. A lack 
of tumorigenic responses at exposure levels that cause significant 
impairment of animal survival may also not be acceptable. In addition, 
overt toxicity or qualitatively altered toxicokinetics due to 
excessively high doses may result in tumor effects that are secondary 
to the toxicity rather than directly attributable to the agent.
    With regard to the appropriateness of the high dose, an adequate 
high dose would generally be one that produces some toxic effects 
without unduly affecting mortality from effects other than cancer or 
producing significant adverse effects on the nutrition and health of 
the test animals (OECD, 1981; NRC, 1993a). If the test agent does not 
appear to cause any specific target organ toxicity or perturbation of 
physiological function, an adequate high dose can be specified in terms 
of a percentage reduction of body weight gain over the lifespan of the 
animals. The high dose would generally be considered inadequate if 
neither toxicity nor change in weight gain is observed. On the other 
hand, significant increases in mortality from effects other than cancer 
generally indicate that an adequate high dose has been exceeded.
    Other signs of treatment-related toxicity associated with an 
excessive high dose may include (a) Significant reduction of body 
weight gain (e.g., greater than 10%), (b) significant increases in 
abnormal behavioral and clinical signs, (c) significant changes in 
hematology or clinical chemistry, (d) saturation of absorption and 
detoxification mechanisms, or (e) marked changes in organ weight, 
morphology, and histopathology. It should be noted that practical upper 
limits have been established to avoid the use of excessively high doses 
in long-term carcinogenicity studies of environmental chemicals (e.g., 
5% of the test substance in the feed for dietary studies or 1 g/kg body 
weight for oral gavage studies [OECD, 1981]).
    For dietary studies, weight gain reductions should be evaluated as 
to whether there is a palatability problem or an issue with food 
efficiency; certainly, the latter is a toxic manifestation. In the case 
of inhalation studies with respirable particles, evidence of impairment 
of normal clearance of particles from the lung should be considered 
along with other signs of toxicity to the respiratory airways to 
determine whether the high exposure concentration has been 
appropriately selected (U.S. EPA, 2001a). For dermal studies, evidence 
of skin irritation may indicate that an adequate high dose has been 
reached (U.S. EPA, 1989).
    In order to obtain the most relevant information from a long-term 
carcinogenicity study, it is important to maximize exposure conditions 
to the test material. At the same time, caution is appropriate in using 
excessive high-dose levels that would confound the interpretation of 
study results to humans. The middle and lowest doses should be selected 
to characterize the shape of the dose-response curve as much as 
possible. It is important that the doses be adequately spaced so that 
the study can provide relevant dose-response data for assessing human 
hazard and risk. If the testing of potential carcinogenicity is being 
combined with an evaluation of noncancer chronic toxicity, the study 
should be designed to include one dose in addition to the control(s) 
that is not expected to elicit adverse effects.
    There are several possible outcomes regarding the study 
interpretation of the significance and relevance of tumorigenic effects 
associated with exposure or dose levels below, at, or above an adequate 
high dose. The general guidance is given here; for each case, the 
information at hand should be evaluated and a rationale should be given 
for the position taken.
     Adequately high dose. If an adequately high dose has been 
used, tumor effects are judged positive or negative depending on the 
presence or absence of significant tumor incidence increases, 
respectively.
     Excessively high dose. If toxicity or mortality is 
excessive at the high dose, interpretation depends on whether or not 
tumors are found.

--Studies that show tumor effects only at excessive doses may be 
compromised and may or may not carry weight, depending on the 
interpretation in the context of other study results and other lines of 
evidence. Results of such studies, however, are generally not 
considered suitable for dose-response extrapolation if it is determined 
that the mode(s) of action underlying the tumorigenic responses at high 
doses is not operative at lower doses.
--Studies that show tumors at lower doses, even though the high dose is 
excessive and may be discounted, should be evaluated on their own 
merits.
--If a study does not show an increase in tumor incidence at a toxic 
high dose and appropriately spaced lower doses are used without such 
toxicity or tumors, the study is generally judged as negative for 
carcinogenicity.

     Inadequately high dose. Studies of inadequate sensitivity 
where an adequately high dose has not been reached may be used to bound 
the dose range where carcinogenic effects might be expected.
2.2.2.1.2. Statistical Considerations
    The main aim of statistical evaluation is to determine whether 
exposure to the test agent is associated with an increase of tumor 
development. Statistical analysis of a long-term study should be 
performed for each tumor type separately. The incidence of benign and 
malignant lesions of the same cell type, usually within a single tissue 
or organ, are considered separately but may be combined when 
scientifically defensible (McConnell et al., 1986).
    Trend tests and pairwise comparison tests are the recommended tests 
for determining whether chance, rather than a treatment-related effect, 
is a plausible explanation for an apparent increase in tumor incidence. 
A trend test such as the Cochran-Armitage test (Snedecor and Cochran, 
1967) asks whether the results in all dose groups together increase as 
dose increases. A pairwise comparison test such as the

[[Page 17783]]

Fisher exact test (Fisher, 1950) asks whether an incidence in one dose 
group is increased over that of the control group. By convention, for 
both tests a statistically significant comparison is one for which p is 
less than 0.05 that the increased incidence is due to chance. 
Significance in either kind of test is sufficient to reject the 
hypothesis that chance accounts for the result.
    A statistically significant response may or may not be biologically 
significant and vice versa. The selection of a significance level is a 
policy choice based on a trade-off between the risks of false positives 
and false negatives. A result with a significance level of greater or 
less than 5% (the most common significance level) is examined to see if 
the result confirms other scientific information. When the assessment 
departs from a simple 5% level, this should be highlighted in the risk 
characterization. A two-tailed test or a one-tailed test can be used. 
In either case a rationale is provided.
    Statistical power can affect the likelihood that a statistically 
significant result could reasonably be expected. This is especially 
important in studies or dose groups with small sample sizes or low dose 
rates. Reporting the statistical power can be useful for comparing and 
reconciling positive and negative results from different studies.
    Considerations of multiple comparisons should also be taken into 
account. Haseman (1983) analyzed typical animal bioassays that tested 
both sexes of two species and concluded that, because of multiple 
comparisons, a single tumor increase for a species-sex-site combination 
that is statistically significant at the 1% level for common tumors or 
5% for rare tumors corresponds to a 7-8% significance level for the 
study as a whole. Therefore, animal bioassays presenting only one 
significant result that falls short of the 1% level for a common tumor 
should be treated with caution.
2.2.2.1.3. Concurrent and Historical Controls
    The standard for determining statistical significance of tumor 
incidence comes from a comparison of tumors in dosed animals with those 
in concurrent control animals. Additional insights about both 
statistical and biological significance can come from an examination of 
historical control data (Tarone, 1982; Haseman, 1995). Historical 
control data can add to the analysis, particularly by enabling 
identification of uncommon tumor types or high spontaneous incidence of 
a tumor in a given animal strain. Identification of common or uncommon 
situations prompts further thought about the meaning of the response in 
the current study in context with other observations in animal studies 
and with other evidence about the carcinogenic potential of the agent. 
These other sources of information may reinforce or weaken the 
significance given to the response in the hazard assessment. Caution 
should be exercised in simply looking at the ranges of historical 
responses, because the range ignores differences in survival of animals 
among studies and is related to the number of studies in the database.
    In analyzing results for uncommon tumors in a treated group that 
are not statistically significant in comparison with concurrent 
controls, the analyst may be informed by the experience of historical 
controls to conclude that the result is in fact unlikely to be due to 
chance. However, caution should be used in interpreting results. In 
analyzing results for common tumors, a different set of considerations 
comes into play. Generally speaking, statistically significant 
increases in tumors should not be discounted simply because incidence 
rates in the treated groups are within the range of historical controls 
or because incidence rates in the concurrent controls are somewhat 
lower than average. Random assignment of animals to groups and proper 
statistical procedures provide assurance that statistically significant 
results are unlikely to be due to chance alone. However, caution should 
be used in interpreting results that are barely statistically 
significant or in which incidence rates in concurrent controls are 
unusually low in comparison with historical controls.
    In cases where there may be reason to discount the biological 
relevance to humans of increases in common animal tumors, such 
considerations should be weighed on their own merits and clearly 
distinguished from statistical concerns.
    When historical control data are used, the discussion should 
address several issues that affect comparability of historical and 
concurrent control data, such as genetic drift in the laboratory 
strains, differences in pathology examination at different times and in 
different laboratories (e.g., in criteria for evaluating lesions; 
variations in the techniques for the preparation or reading of tissue 
samples among laboratories), and comparability of animals from 
different suppliers. The most relevant historical data come from the 
same laboratory and the same supplier and are gathered within 2 or 3 
years one way or the other of the study under review; other data should 
be used only with extreme caution.
2.2.2.1.4. Assessment of Evidence of Carcinogenicity From Long-term 
Animal Studies
    In general, observation of tumors under different circumstances 
lends support to the significance of the findings for animal 
carcinogenicity. Significance is generally increased by the observation 
of more of the factors listed below. For a factor such as malignancy, 
the severity of the observed pathology can also affect the 
significance. The following observations add significance to the tumor 
findings:
     Uncommon tumor types;
     Tumors at multiple sites;
     Tumors by more than one route of administration;
     Tumors in multiple species, strains, or both sexes;
     Progression of lesions from preneoplastic to benign to 
malignant;
     Reduced latency of neoplastic lesions;
     Metastases;
     Unusual magnitude of tumor response;
     Proportion of malignant tumors; and
     Dose-related increases.
    In these cancer guidelines, tumors observed in animals are 
generally assumed to indicate that an agent may produce tumors in 
humans. Mode of action may help inform this assumption on a chemical-
specific basis. Moreover, the absence of tumors in well-conducted, 
long-term animal studies in at least two species provides reasonable 
assurance that an agent may not be a carcinogenic concern for humans.
2.2.2.1.5. Site Concordance
    Site concordance of tumor effects between animals and humans should 
be considered in each case. Thus far, there is evidence that growth 
control mechanisms at the level of the cell are homologous among 
mammals, but there is no evidence that these mechanisms are site 
concordant. Moreover, agents observed to produce tumors in both humans 
and animals have produced tumors either at the same site (e.g., vinyl 
chloride) or different sites (e.g., benzene)(NRC, 1994). Hence, site 
concordance is not always assumed between animals and humans. On the 
other hand, certain modes of action with consequences for particular 
tissue sites (e.g., disruption of thyroid function) may lead to an 
anticipation of site concordance.
2.2.2.2. Perinatal Carcinogenicity Studies
    The objective of perinatal carcinogenesis studies is to determine

[[Page 17784]]

the carcinogenic potential and dose-response relationships of the test 
agent in the developing organism. Some investigators have hypothesized 
that the age of initial exposure to a chemical carcinogen may influence 
the carcinogenic response (Vesselinovitch et al., 1979; Rice, 1979; 
McConnell, 1992). Current standardized long-term carcinogenesis 
bioassays generally begin dosing animals at 6-8 weeks of age and 
continue dosing for the lifespan of the animal (18-24 months). This 
protocol has been modified in some cases to investigate the potential 
of the test agent to induce transplacental carcinogenesis or to 
investigate the potential differences following perinatal and adult 
exposures, but currently there is not a standardized protocol for 
testing agents for carcinogenic effects following prenatal or early 
postnatal exposure.
    Several cancer bioassay studies have compared adult and perinatal 
exposures (see McConnell, 1992; U.S. EPA, 1996b). A review of these 
studies reveals that perinatal exposure rarely identifies carcinogens 
that are not found in standard animal bioassays. Exposure that is 
perinatal can increase the incidence of a given type of tumor. The 
increase may reflect an increased length of exposure and a higher dose 
for the developing organism relative to the adult or an increase in 
susceptibility in some cases. Additionally, exposure that is perinatal 
through adulthood sometimes reduces the latency period for tumors to 
develop in the growing organism (U.S. EPA, 1996b). EPA evaluates the 
usefulness of perinatal studies on an agent-by-agent basis (e.g., U.S. 
EPA, 1997a, b).
    Perinatal study data analysis generally follows the principles 
discussed above for evaluating other long-term carcinogenicity studies. 
When differences in responses between perinatal animals and adult 
animals suggest an increased susceptibility of perinatal or postnatal 
animals, such as the ones below, a separate evaluation of the response 
should be prepared:
     A difference in dose-response relationship,
     The presence of different tumor types,
     An earlier onset of tumors, or
     An increase in the incidence of tumors.
2.2.2.3. Other Studies
    Intermediate-term and acute dosing studies often use protocols that 
screen for carcinogenic or preneoplastic effects, sometimes in a single 
tissue. Some protocols involve the development of various proliferative 
lesions, such as foci of alteration in the liver (Goldsworthy et al., 
1986). Others use tumor endpoints, such as the induction of lung 
adenomas in the sensitive strain A mouse (Maronpot et al., 1986) or 
tumor induction in initiation-promotion studies using various organs 
such as the bladder, intestine, liver, lung, mammary gland, and thyroid 
(Ito et al., 1992). In these tests, the selected tissue rather than the 
whole animal is, in a sense, the test system. Important information 
concerning the steps in the carcinogenic process and mode of action can 
be obtained from ``start/stop'' experiments. In these protocols, an 
agent is given for a period of time to induce particular lesions or 
effects and then stopped in order to evaluate the progression or 
reversibility of processes (Todd, 1986; Marsman and Popp, 1994).
    Assays in genetically engineered rodents may provide insight into 
the chemical and gene interactions involved in carcinogenesis (Tennant 
et al., 1995). These mechanistically based approaches involve activated 
oncogenes that are introduced (transgenic) or tumor suppressor genes 
that are deleted (knocked out). If appropriate genes are selected, not 
only may these systems provide information on mechanisms, but the 
rodents typically show tumor development earlier than in the standard 
bioassay. Transgenic mutagenesis assays also represent a mechanistic 
approach for assessing the mutagenic properties of agents as well as 
developing quantitative linkages between exposure, internal dose, and 
mutation related to tumor induction (Morrison and Ashby, 1994; Sisk et 
al., 1994; Hayward et al., 1995).
    The support that these studies give to a determination of 
carcinogenicity rests on their contribution to the consistency of other 
evidence about an agent. For instance, benzoyl peroxide has promoter 
activity on the skin, but the overall evidence may be less supportive 
(Kraus et al., 1995). These studies also may contribute information 
about mode of action. It is important to recognize the limitations of 
these experimental protocols, such as short duration, limited 
histology, lack of complete development of tumors, or experimental 
manipulation of the carcinogenic process, that may limit their 
contribution to the overall assessment. Generally, their results are 
appropriate as aids in the interpretation of other toxicological 
evidence (e.g., rodent chronic bioassays), especially regarding 
potential modes of action. On the basis of currently available 
information, it is unlikely that any of these assays, which are 
conducted for 6 months with 15 animals per group, will replace all 
chronic bioassays for hazard identification (Spalding et al., 2000; 
Gulezian et al., 2000; ILSI, 2001).
2.2.3. Structural Analogue Data
    For some chemical classes, there is significant available 
information, largely from rodent bioassays, on the carcinogenicity of 
analogues. Analogue effects are instructive in investigating 
carcinogenic potential of an agent as well as in identifying potential 
target organs, exposures associated with effects, and potential 
functional class effects or modes of action. All appropriate studies 
should be included and analyzed, whether indicative of a positive 
effect or not. Evaluation includes tests in various animal species, 
strains, and sexes; with different routes of administration; and at 
various doses, as data are available. Confidence in conclusions is a 
function of how similar the analogues are to the agent under review in 
structure, metabolism, and biological activity. It is important to 
consider this confidence to ensure a balanced position.

2.3. Analysis of Other Key Data

    The physical, chemical, and structural properties of an agent, as 
well as data on endpoints that are thought to be critical elements of 
the carcinogenic process, provide valuable insights into the likelihood 
of human cancer risk. The following sections provide guidance for 
analyses of these data.
2.3.1. Physicochemical Properties
    Physicochemical properties affect an agent's absorption, tissue 
distribution (bioavailability), biotransformation, and degradation in 
the body and are important determinants of hazard potential (and dose-
response analysis). Properties that should be analyzed include, but are 
not limited to, molecular weight, size, and shape; valence state; 
physical state (gas, liquid, solid); water or lipid solubility, which 
can influence retention and tissue distribution; and potential for 
chemical degradation or stabilization in the body.
    An agent's potential for chemical reaction with cellular 
components, particularly with DNA and proteins, is also important. The 
agent's molecular size and shape, electrophilicity, and charge 
distribution are considered in order to decide whether they would 
facilitate such reactions.
2.3.2. Structure-Activity Relationships (SARs)
    SAR analyses and models can be used to predict molecular 
properties, surrogate biological endpoints, and carcinogenicity (see, 
e.g., Richard, 1998a, b; Richard and Williams, 2002;

[[Page 17785]]

Contrera et al., 2003). Overall, these analyses provide valuable 
initial information on agents, they may strengthen or weaken concern, 
and they are part of the weight of evidence.
    Currently, SAR analysis is most useful for chemicals and 
metabolites that are believed to initiate carcinogenesis through 
covalent interaction with DNA (i.e., DNA-reactive, mutagenic, 
electrophilic, or proelectrophilic chemicals) (Ashby and Tennant, 
1991). For organic chemicals, the predictive capability of SAR analysis 
combined with other toxicity information has been demonstrated (Ashby 
and Tennant, 1994). The following parameters are useful in comparing an 
agent to its structural analogues and congeners that produce tumors and 
affect related biological processes such as receptor binding and 
activation, mutagenicity, and general toxicity (Woo and Arcos, 1989):
     Nature and reactivity of the electrophilic moiety or 
moieties present;
     Potential to form electrophilic reactive intermediate(s) 
through chemical, photochemical, or metabolic activation;
     Contribution of the carrier molecule to which the 
electrophilic moiety(ies) is attached;
     Physicochemical properties (e.g., physical state, 
solubility, octanol/water partition coefficient, half-life in aqueous 
solution);
     Structural and substructural features (e.g., electronic, 
stearic, molecular geometric);
     Metabolic pattern (e.g., metabolic pathways and activation 
and detoxification ratio); and
     Possible exposure route(s) of the agent.
    Suitable SAR analysis of non-DNA-reactive chemicals and of DNA-
reactive chemicals that do not appear to bind covalently to DNA should 
be based on knowledge or postulation of the probable mode(s) of action 
of closely related carcinogenic structural analogues (e.g., receptor 
mediated, cytotoxicity related). Examination of the physicochemical and 
biochemical properties of the agent may then provide the rest of the 
information needed in order to make an assessment of the likelihood of 
the agent's activity by that mode of action.
2.3.3. Comparative Metabolism and Toxicokinetics
    Studies of the absorption, distribution, biotransformation, and 
excretion of agents permit comparisons among species to assist in 
determining the implications of animal responses for human hazard 
assessment, supporting identification of active metabolites, 
identifying changes in distribution and metabolic pathway or pathways 
over a dose range, and making comparisons among different routes of 
exposure.
    If extensive data are available (e.g., blood/tissue partition 
coefficients and pertinent physiological parameters of the species of 
interest), physiologically based toxicokinetic models can be 
constructed to assist in a determination of tissue dosimetry, species-
to-species extrapolation of dose, and route-to-route extrapolation 
(Conolly and Andersen, 1991; see Section 3.1.2). If sufficient data are 
not available, it may be assumed as a default that toxicokinetic and 
metabolic processes are qualitatively comparable among species. 
Discussion of appropriate procedures for quantitative, interspecies 
comparisons appears in Chapter 3.
    The qualitative question of whether an agent is absorbed by a 
particular route of exposure is important for weight of evidence 
classification, discussed in Section 2.5. Decisions about whether route 
of exposure is a limiting factor on expression of any hazard, e.g., 
absorption does not occur by a specified route, are generally based on 
studies in which effects of the agent or its structural analogues have 
been observed by different routes, on physical-chemical properties, or 
on toxicokinetics studies.
    Adequate metabolism and toxicokinetic data can be applied toward 
the following, as data permit. Confidence in conclusions is enhanced 
when in vivo data are available.
     Identifying metabolites and reactive intermediates of 
metabolism and determining whether one or more of these intermediates 
is likely to be responsible for the observed effects. Information on 
the reactive intermediates focuses on SAR analysis, analysis of 
potential modes of action, and estimation of internal dose in dose-
response assessment (D'Souza et al., 1987; Krewski et al., 1987).
     Identifying and comparing the relative activities of 
metabolic pathways in animals and in humans, and at different ages. 
This analysis can provide insights for extrapolating results of animal 
studies to humans.
     Describing anticipated distribution within the body and 
possibly identifying target organs. Use of water solubility, molecular 
weight, and structure analysis can support qualitative inferences about 
anticipated distribution and excretion. In addition, describing whether 
the agent or metabolite of concern will be excreted rapidly or slowly 
or whether it will be stored in a particular tissue or tissues to be 
mobilized later can identify issues in comparing species and 
formulating dose-response assessment approaches.
     Identifying changes in toxicokinetics and metabolic 
pathways with increases in dose. These changes may result in important 
differences between high and low dose levels in disposition of the 
agent or generation of its active forms. These studies play an 
important role in providing a rationale for dose selection in 
carcinogenicity studies.
     Identifying and comparing metabolic process differences by 
age, sex, or other characteristic so that susceptible subpopulations 
can be recognized. For example, metabolic capacity with respect to P450 
enzymes in newborn children is extremely limited compared to that in 
adults, so that a carcinogenic metabolite formed through P450 activity 
will have limited effect in the young, whereas a carcinogenic agent 
deactivated through P450 activity will result in increased 
susceptibility of this lifestage (Cresteil, 1998). A variety of changes 
in toxicokinetics and physiology occur from the fetal stage to post-
weaning to young child. Any of these changes may make a difference for 
risk (Renwick, 1998).
     Determining bioavailability via different routes of 
exposure by analyzing uptake processes under various exposure 
conditions. This analysis supports identification of hazards for 
untested routes. In addition, use of physicochemical data (e.g., 
octanol-water partition coefficient information) can support an 
inference about the likelihood of dermal absorption (Flynn, 1990).
    Attempts should be made in all of these areas to clarify and 
describe as much as possible the variability to be expected because of 
differences in species, sex, age, and route of exposure. The analysis 
takes into account the presence of subpopulations of individuals who 
are particularly vulnerable to the effects of an agent because of 
toxicokinetic or metabolic differences (genetically or environmentally 
determined) (Bois et al., 1995) and is a special emphasis for 
assessment of risks to children.
2.3.4. Toxicological and Clinical Findings
    Toxicological findings in experimental animals and clinical 
observations in humans are important resources for the cancer hazard 
assessment. Such findings provide information on physiological effects 
and effects on enzymes, hormones, and other important macromolecules as 
well

[[Page 17786]]

as on target organs for toxicity. For example, given that the cancer 
process represents defects in processes such as terminal 
differentiation, growth control, and cell death, developmental studies 
of agents may provide an understanding of the activity of an agent that 
carries over to cancer assessment. Toxicity studies in animals by 
different routes of administration support comparison of absorption and 
metabolism by those routes. Data on human variability in standard 
clinical tests may also provide insight into the range of human 
susceptibility and the common mechanisms of agents that affect the 
tested parameters.
2.3.5. Events Relevant to Mode of Carcinogenic Action
    Knowledge of the biochemical and biological changes that precede 
tumor development (which include, but are not limited to, mutagenesis, 
increased cell proliferation, inhibition of programmed cell death, and 
receptor activation) may provide important insight for determining 
whether a cancer hazard exists and may help inform appropriate 
consideration of the dose-response relationship below the range of 
observable tumor response. Because cancer can result from a series of 
genetic alterations in the genes that control cell growth, division, 
and differentiation (Vogelstein et al., 1988; Hanahan and Weinberg, 
2000; Kinzler and Vogelstein, 2002), the ability of an agent to affect 
genotype (and hence gene products) or gene expression is of obvious 
importance in evaluating its influence on the carcinogenic process. 
Initial and key questions to examine are: Does the agent (or its 
metabolite) interact directly with DNA, leading to mutations that bring 
about changes in gene products or gene expression? Does the agent bring 
about effects on gene expression via other nondirect DNA interaction 
processes?
    Furthermore, carcinogenesis involves a complex series and interplay 
of events that alter the signals a cell receives from its extracellular 
environment, thereby promoting uncontrolled growth. Many, but not all, 
mutagens are carcinogens, and some, but not all, agents that induce 
cell proliferation lead to tumor development. Thus, understanding the 
range of key steps in the carcinogenic process upon which an agent 
might act is essential for evaluating its mode of action. Determination 
of carcinogens that are operating by a mutagenic mode of action, for 
example, entails evaluation of in vivo or in vitro short-term testing 
results for genetic endpoints, metabolic profiles, physicochemical 
properties, and structure-activity relationship (SAR) analyses in a 
weight-of-evidence approach (Dearfield et al., 1991; U.S. EPA, 1986b; 
Waters et al., 1999). Key data for a mutagenic mode of action may be 
evidence that the carcinogen or a metabolite is DNA-reactive and/or has 
the ability to bind to DNA. Also, mutagenic carcinogens usually produce 
positive effects in multiple test systems for different genetic 
endpoints, particularly gene mutations and structural chromosome 
aberrations, and in tests performed in vivo which generally are 
supported by positive tests in vitro. Additionally, carcinogens may be 
identified as operating via a mutagenic mode of action if they have 
similar properties and SAR to mutagenic carcinogens. Endpoints that 
provide insight into an agent's ability to alter gene products and gene 
expression, together with other features of an agent's potential mode 
of carcinogenic action, are discussed below.
2.3.5.1. Direct DNA-Reactive Effects
    It is well known that many carcinogens are electrophiles that 
interact with DNA, resulting in DNA adducts and breakage (referred to 
in these cancer guidelines as direct DNA effects). Usually during the 
process of DNA replication, these DNA lesions can be converted into and 
fixed as mutations and chromosomal alterations that then may initiate 
and otherwise contribute to the carcinogenic process (Shelby and 
Zeiger, 1990; Tinwell and Ashby, 1991; IARC, 1999). Thus, studies of 
mutations and other genetic lesions continue to inform the assessment 
of potential human cancer hazard and in the understanding of an agent's 
mode of carcinogenic action.
    EPA has published testing guidelines for detecting the ability of 
an agent to damage DNA and produce mutations and chromosomal 
alterations (as discussed in Dearfield et al., 1991). Briefly, standard 
tests for gene mutations in bacteria and mammalian cells in vitro and 
in vivo and for structural chromosomal aberrations in vitro and in vivo 
are important examples of relevant methods. New molecular approaches, 
such as mouse mutations and cancer transgenic models, are providing a 
means to examine mutation at tissue sites where the tumor response is 
observed (Heddle and Swiger, 1996; Tennant et al., 1999). Additionally, 
continued improvements in fluorescent-based chromosome staining methods 
(fluorescent in situ hybridization [FISH]) will allow the detection of 
specific chromosomal abnormalities in relevant target tissues (Tucker 
and Preston, 1998).
    Endpoints indicative of DNA damage but not measures of mutation per 
se, such as DNA adducts or strand breakage, may be detected in relevant 
target tissues and thus contribute to evaluating an agent's mutagenic 
potential. Evidence of chemical-specific DNA adducts (e.g., reactions 
at oxygen sites in DNA bases or with ring nitrogens of guanine and 
adenine) provides information on a mutagen's ability to directly 
interact with DNA (La and Swenberg, 1996). Some planar molecules (e.g., 
9-aminoacridine) intercalate between base pairs of DNA, which results 
in a physical distortion in DNA that may lead to mutations when DNA 
replicates. As discussed below, some carcinogens do not interact 
directly with DNA, but they can produce increases in endogenous levels 
of DNA adducts (e.g., 8-hydroxyguanine) by indirect mechanisms.
2.3.5.2. Indirect DNA Effects or Other Effects on Genes/Gene Expression
    Although some carcinogens may result in an elevation of mutations 
or cytogenetic anomalies, as detected in standard assays, they may do 
so by indirect mechanisms. These effects may be brought about by 
chemical-cell interactions rather than by the chemical (or its 
metabolite) directly interacting with DNA. An increase in mutations 
might be due to cytotoxic exposures causing regenerative proliferation 
or to mitogenic influences (Cohen and Ellwein, 1990). Increased cell 
division may elevate mutation by clonal expansion of initiated cells or 
by increasing the number of genetic errors by rapid cell division and 
reduced time for DNA repair. Some agents might result in an elevation 
of mutations by interfering with the enzymes involved in DNA repair and 
recombination (Barrett and Lee, 1992). Damage to certain critical DNA 
repair genes or other genes (e.g., the p53 gene) may result in genomic 
instability, which predisposes cells to further genetic alterations and 
increases the probability of neoplastic progression (Harris and 
Hollstein, 1993; Levine et al., 1994; Rouse and Jackson, 2002). 
Likewise, DNA repair processes may be saturated at certain doses of a 
chemical, leading to an elevation of genetic alterations.
    The initiation of programmed cell death (apoptosis) can potentially 
be blocked by an agent, thereby permitting replication of cells 
carrying genetic errors that would normally be removed from the 
proliferative pool. At certain doses an agent may also generate 
reactive oxygen species that produce oxidative damage to DNA and other

[[Page 17787]]

macromolecules (Chang et al. 1988; Kehrer, 1993; Clayson et al., 1994). 
The role of cellular alterations that are attributable to oxidative 
damage in tumorigenesis (e.g., 8-hydroxyguanine) is currently unclear.
    Several carcinogens have been shown to induce aneuploidy (the loss 
or gain of chromosomes) (Barrett, 1992; Gibson et al., 1995). 
Aneuploidy can result in the loss of heterozygosity or genomic 
instability (Cavenee et al., 1986; Fearon and Vogelstein, 1990). Agents 
that cause aneuploidy typically interfere with the normal process of 
chromosome segregation by interacting with non-DNA targets such as the 
proteins needed for chromosome segregation and chromosome movement. 
Whether this chromosome imbalance is the cause or the effect of 
tumorigenesis is not clear. Thus, it is important to understand if the 
agent induces aneuploidy as a key early event in the carcinogenic 
process.
    It is possible for an agent to alter gene expression by 
transcriptional, translational, or post-translational modifications. 
For example, perturbation of DNA methylation patterns may cause effects 
that contribute to carcinogenesis (Jones, 1986; Holliday, 1987; Goodman 
and Counts, 1993; Chuang et al., 1996; Baylin and Bestor, 2002). 
Overexpression of genes by DNA amplification has been observed in 
certain tumors (Vainio et al., 1992). Mechanisms of altering gene 
expression may involve cellular reprogramming through hormonal or 
receptor-mediated mechanisms (Barrett, 1992; Ashby et al., 1994).
    Both cell proliferation and programmed cell death can be part of 
the maintenance of homeostasis in many normal tissues, and alterations 
in the level or rate of either can be important elements of the 
carcinogenic process. The balance between the two can directly affect 
the survival and growth of initiated cells as well as preneoplastic and 
tumor cell populations (i.e., increase in cell proliferation or 
decrease in cell death) (Moolgavkar, 1986; Cohen and Ellwein, 1990, 
1991; Cohen et al., 1991; Bellamy et al., 1995). Thus, measurements of 
these events can contribute to the weight of the evidence for cancer 
hazard prediction and to mode of action understanding. In studies of 
proliferative effects, distinctions should be made between mitogenesis 
and regenerative proliferation (Cohen and Ellwein, 1990, 1991; Cohen et 
al., 1991).
    In applying information from studies on cell proliferation and 
apoptosis to risk assessment, it is important to identify the tissues 
and target cells involved, to measure effects in both normal and 
neoplastic tissue, to distinguish between apoptosis and necrosis, and 
to determine the dose that affects these processes. Gap-junctional 
intercellular communication is believed to play a role in tissue and 
organ development and in the maintenance of a normal cellular phenotype 
within tissues. A growing body of evidence suggests that chemical 
interference with gap-junctional intercellular communication is a 
contributing factor in tumor development (Swierenga and Yamasaki, 1992; 
Yamasaki, 1995).
2.3.5.3. Precursor Events and Biomarker Information
    Most testing schemes for mutagenicity and other short-term assays 
were designed for hazard identification purposes; thus, these assays 
are generally conducted using acute exposures. For data on ``precursor 
steps'' to be useful in informing the dose-response curve for tumor 
induction below the level of observation, it is often useful for data 
to come from in vivo studies and from studies where exposure is 
repeated or given over an extended period of time. Although consistency 
of results across different assays and animal models provides a 
stronger basis for drawing conclusions, it is desirable to have data on 
the precursor event in the same target organ, sex, animal strain, and 
species as the tumor data. In evaluating an agent's mode of action, it 
is usually not sufficient to determine that some event commences upon 
dosing. It is important to understand whether it is a necessary event 
that plays a key role in the process that leads to tumor development 
versus an effect of the cancer process itself or simply an associated 
event.
    Various endpoints can serve as biological markers of effects in 
biological systems or samples. These may help identify doses at which 
elements of the carcinogenic process are operating; aid in interspecies 
extrapolations when data are available from both experimental animal 
and human cells; and under certain circumstances, provide insights into 
the possible shape of the dose-response curve below levels where tumor 
incidences are observed (e.g., Choy, 1993).
    Genetic and other findings (such as changes in proto-oncogenes and 
tumor suppressor genes in preneoplastic and neoplastic tissue or, 
possibly, measures of endocrine disruption) can indicate the potential 
for disease and, as such, serve as biomarkers of effect. They, too, can 
be used in different ways.
     The spectrum of genetic changes in proliferative lesions 
and tumors following chemical administration to experimental animals 
can be determined and compared with that in spontaneous tumors in 
control animals, in animals exposed to other agents of varying 
structural and functional activities, and in persons exposed to the 
agent under study.
     Biomarkers of effect and/or precursors may help to 
identify subpopulations of individuals who may be at an elevated risk 
for a certain cancer or exposure to a certain agent, e.g., cytochrome 
P450 2D6/debrisoquine sensitivity for lung cancer (Caporaso et al., 
1989) or inherited colon cancer syndromes (Kinzler et al., 1991; 
Peltom[auml]ki et al., 1993).
     As with biomarkers of exposure, it may be justified in 
some cases to use biomarkers of effect and/or precursors for dose-
response assessment or to provide insight into the potential shape of 
the dose-response curve at doses below those at which tumors are 
induced experimentally.
    In applying biomarker data to cancer assessment an assessment 
should consider:
     Analytical methodology,
     Routes of exposure,
     Exposure to mixtures,
     Time after exposure,
     Sensitivity and specificity of biomarkers, and
     Dose-response relationships.
2.3.5.4. Judging Data
    Criteria that are generally applicable for judging the adequacy of 
mechanistically based data include:
     Mechanistic relevance of the data to carcinogenicity,
     Number of studies of each endpoint,
     Consistency of results in different test systems and 
different species,
     Similar dose-response relationships for tumor and mode of 
action-related effects,
     Conduct of the tests in accordance with generally accepted 
protocols, and
     Degree of consensus and general acceptance among 
scientists regarding interpretation of the significance and specificity 
of the tests.
    Although important information can be gained from in vitro test 
systems, a higher level of confidence is generally given to data that 
are derived from in vivo systems, particularly those results that show 
a site concordance with the tumor data.
    It is important to remember that when judging and considering the 
use of any data, the basic standard of quality, as defined by the EPA 
Information Quality Guidelines, should be satisfied.

[[Page 17788]]

2.4. Mode of Action--General Considerations and Framework for Analysis

2.4.1. General Considerations
    The interaction between the biology of the organism and the 
chemical properties of the agent determine whether there is an adverse 
effect. Thus, mode of action analysis is based on physical, chemical, 
and biological information that helps to explain key events in an 
agent's influence on development of tumors. The entire range of 
information developed in the assessment is reviewed to arrive at a 
reasoned judgment. An agent may work by more than one mode of action, 
both at different sites and at the same tumor site. Thus the mode of 
action and human relevance cannot necessarily be generalized to other 
toxic endpoints or tissues or cell types without additional analyses 
(IPCS, 1999; Meek et al., 2003). At least some information bearing on 
mode of action (e.g., SAR, screening tests for mutagenicity) is present 
for most agents undergoing assessment of carcinogenicity, even though 
certainty about exact molecular mechanisms may be rare.
    Information for mode of action analysis generally includes tumor 
data in humans and animals and among structural analogues, as well as 
the other key data. The more complete the data package and the generic 
knowledge about a given mode of action, the more confidence one has and 
the more one can rely on assessment of available data rather than 
reverting to default options to address the absence of information on 
mode of action. Reasoned judgments are generally based on a data-rich 
source of chemical, chemical class, and tumor type-specific 
information. Many times there will be conflicting data and gaps in the 
information base; it is important to carefully evaluate these 
uncertainties before reaching any conclusion.
    In making decisions about potential modes of action and the 
relevance of animal tumor findings to humans (Ashby et al., 1990; Ashby 
and Tennant, 1991; Tennant, 1993; IPCS 1999; Sonich-Mullin et al., 
2001; Meek et al., 2003), very often the results of chronic animal 
studies may give important clues. Some of the important factors to 
review include:
     Tumor types, for example, those responsive to endocrine 
influence or those produced by DNA-reactive carcinogens;
     Number of studies and of tumor sites, sexes, and species 
affected or unaffected in those studies and if the data present a 
coherent story;
     Similarity of metabolic activation and detoxification for 
a specific chemical between humans and tested species;
     Influence of route of exposure on the spectrum of tumors 
and whether they occur at point of exposure or systemic sites;
     Effect of high dose exposures on the target organ or 
systemic toxicity that may not reflect typical physiological 
conditions, for example, urinary chemical changes associated with stone 
formation, effects on immune surveillance;
     Presence of proliferative lesions, for example, hepatic 
foci, or hyperplasia;
     Effect of dose and time on the progression of lesions from 
preneoplastic to benign tumors, then to malignant;
     Ratio of malignant to benign tumors as a function of dose 
and time;
     Time of appearance of tumors after commencing exposure;
     Development of tumors that invade locally or systemically, 
or lead to death;
     Tumors at organ sites with high or low background 
historical incidence in laboratory animals;
     Biomarkers in tumor cells, both induced and spontaneous, 
for example, DNA or protein adducts, mutation spectra, chromosome 
changes, oncogene activation; and/or
     Shape of the dose-response curve in the range of tumor 
observation, for example, linear versus nonlinear.
    Some of the myriad ways in which information from chronic animal 
studies influences mode of action judgments include, but are not 
limited to, the following:
     Multisite and multispecies tumor effects that are often 
associated with mutagenic agents;
     Tumors restricted to one sex or species suggesting an 
influence restricted to gender, strain, or species;
     Late onset of tumors that are primarily benign, are at 
sites with a high historical background incidence, or show reversal of 
lesions on cessation of exposure suggesting a growth-promoting mode of 
action;
     The possibility that an agent acting differently in 
different tissues; or
     The possibility that has more than one mode of action in a 
single tissue.
    Simple knowledge of sites of tumor increase in rodent studies can 
give preliminary clues as to mode of action. Experience at the National 
Toxicology Program (NTP) indicates that substances that are DNA 
reactive and that produce gene mutations may be unique in producing 
tumors in certain anatomical sites, whereas tumors at other sites may 
arise from both mutagenic or nonmutagenic influences (Ashby and 
Tennant, 1991; Huff et al., 1991).
    The types of data and their influence on judgments regarding mode 
of action are expected to evolve, both as science advances and as the 
risk assessment community gains more experience with these analyses. 
This section contains a framework for evaluating hypothesized mode(s) 
of action. This framework has similarities to and differences with the 
concepts presented in other MOA frameworks (e.g., IPCS, 1999; Sonich-
Mullin et al., 2001; Meek et al., 2003). Differences are often due to 
the context of the use for the framework. For example, the Meek et al. 
(2003) presents a stand-alone document for addressing mode of action 
issues; thus, it recommends that conclusions concerning MOA be rendered 
separately. In these cancer guidelines, however, they are incorporated 
into the context of all of the data regarding weight of the evidence 
for carcinogenicity.
2.4.2. Evaluating an Hypothesized Mode of Action
2.4.2.1. Peer Review
    In reaching conclusions, the question of ``general acceptance'' of 
a mode of action should be tested as part of the independent peer 
review that EPA obtains for its assessment and conclusions. In some 
cases the mode of action may already have been established by 
development of a large body of research information and 
characterization of the phenomenon over time. In some cases there will 
have been development of an Agency policy (e.g., mode of action 
involving alpha-2u-globulin in the male rat [U.S. EPA, 1991b]) or a 
series of previous assessments in which both the mode of action and its 
applicability to particular cases has been explored. If so, the 
assessment and its peer review can focus on the evidence that a 
particular agent acts in this mode. The peer review should also 
evaluate the strengths and weaknesses of competing modes of action.
    In other cases, the mode of action may not have previously been the 
subject of an Agency document. If so, the data to support both the mode 
of action and the associated activity of the agent should undergo EPA 
assessment and subsequent peer review.
2.4.2.2. Use of the Framework
    The framework supports a full analysis of mode of action 
information, but it can also be used as a screen to decide whether 
sufficient information is available to evaluate or whether the data

[[Page 17789]]

gaps are too substantial to justify further analysis. Mode of action 
conclusions are used to address the question of human relevance of 
animal tumor responses, to address differences in anticipated response 
among humans, such as between children and adults or men and women; and 
as the basis of decisions about the anticipated shape of the dose-
response relationship. Guidance on the latter appears in Section 3.
    This framework is intended to provide an analytical approach for 
evaluating the mode of action. It is neither a checklist nor a list of 
required criteria. As the type and amount of information will depend on 
the mode of action postulated, scientific judgment is important to 
determine if the weight of evidence is sufficient.
2.4.3. Framework for Evaluating Each Hypothesized Carcinogenic Mode of 
Action
    This framework is intended to be an analytic tool for judging 
whether available data support a mode of carcinogenic action 
hypothesized for an agent. It is based upon considerations for 
causality in epidemiologic investigations originally articulated by 
Hill (1965) but later modified by others and extended to experimental 
studies. The original Hill criteria were applied to epidemiologic data, 
whereas this framework is applied to a much wider assortment of 
experimental data, so it retains the basic principles of Hill but is 
much modified in content.
    The modified Hill criteria can be useful for organizing thinking 
about aspects of causation, and they are consistent with the scientific 
method of developing hypotheses and testing those hypotheses 
experimentally. During analysis by EPA, and as guidance for peer 
review, a key question is whether the data to support a mode of action 
meet the standards generally applied in experimental biology regarding 
inference of causation.
    All pertinent studies are reviewed in analyzing a mode of action, 
and an overall weighing of evidence is performed, laying out the 
strengths, weaknesses, and uncertainties of the case as well as 
potential alternative positions and rationales. Identifying data gaps 
and research needs is also part of the assessment.
    To evaluate whether an hypothesized mode of action is operative, an 
analysis starts with an outline of the scientific findings regarding 
the hypothesized key events leading to cancer, and then weighing 
information to determine whether there is a causal relationship between 
these events and cancer formation, i.e., that the effects are critical 
for induction of tumors. It is not generally expected that the complete 
sequence will be known at the molecular level. Instead, empirical 
observations made at different levels of biological organization--
biochemical, cellular, physiological, tissue, organ, and system--are 
analyzed.
    Several important points should be considered when working with the 
framework:
     The topics listed for analysis should not be regarded as a 
checklist of necessary ``proofs.'' The judgment of whether an 
hypothesized mode of action is supported by available data takes 
account of the analysis as a whole.
     The framework provides a structure for organizing the 
facts upon which conclusions as to mode of action rest. The purpose of 
using the framework is to make analysis transparent and to allow the 
reader to understand the facts and reasoning behind a conclusion.
     The framework does not dictate an answer. The weight of 
evidence that is sufficient to support a decision about a mode of 
action may be less or more, depending on the purpose of the analysis, 
for example, screening, research needs identification, or full risk 
assessment. To make the reasoning transparent, the purpose of the 
analysis should be made apparent to the reader.
     Toxicokinetic studies may contribute to mode of action 
analysis by contributing to identifying the active form(s) of an agent 
that is central to the mode of action. Apart from contributing in this 
way, toxicokinetics studies may reveal effects of saturation of 
metabolic processes. These may not be considered key events in a mode 
of action, but they are given separate consideration in assessing dose 
metrics and potential nonlinearity of the dose-response relationship.
     Generally, ``sufficient'' support is a matter of 
scientific judgment in the context of the requirements of the 
decisionmaker or in the context of science policy guidance regarding a 
certain mode of action.
     Even when an hypothesized mode of action is supported for 
a described response in a specific tissue, it may not explain other 
tumor responses observed, which should get separate consideration in 
hazard and dose-response assessment.
    For each tumor site being evaluated, the mode of action analysis 
should begin with a description of the relevant data and key events 
that may be associated with an hypothesized mode of action and its 
sequence of key events (see Section 2.4.3.1). This can be followed by a 
discussion of various aspects of the experimental support for 
hypothesized mode(s) of action in animals and humans (see Section 
2.4.3.2). The possibility of other modes of action also should be 
considered and discussed (see Section 2.4.3.3); if there is evidence 
for more than one mode of action, each should receive a separate 
analysis. Conclusions about each hypothesized mode of action should 
address whether the mode of action is supported in animals and is 
relevant to humans and which populations or lifestages can be 
particularly susceptible (see Section 2.4.3.4). In a risk assessment 
document, the analysis of an hypothesized mode of action can be 
presented before or with the characterization of an agent's potential 
hazard to humans.
2.4.3.1. Description of the Hypothesized Mode of Action
    Summary description of the hypothesized mode of action. For each 
tumor site, the mode of action analysis begins with a description of 
the hypothesized mode of action and its sequence of key events. If 
there is evidence for more than one mode of action, each receives a 
separate analysis.
    Identification of key events. In order to judge how well data 
support involvement of a key event in carcinogenic processes, the 
experimental definition of the event or events should be clear and 
reproducible. To support an association, experiments should define and 
measure an event consistently.
     Can a list of events be identified that are key to the 
carcinogenic process?
     Are the events well defined?
    Pertinent observations may include, but are not limited to, 
receptor-ligand changes, cytotoxicity, cell cycle effects, increased 
cell growth, organ weight differences, histological changes, hormone or 
other protein perturbations, or DNA and chromosome effects.
2.4.3.2. Discussion of the Experimental Support for the Hypothesized 
Mode of Action
    The experimental support for the hypothesized mode of action should 
be discussed from several viewpoints patterned after the Hill criteria 
(see Section 2.2.1.7). For illustration, the explanation of each topic 
includes typical questions to be addressed to the available empirical 
data and experimental observations anticipated to be pertinent. The 
latter will vary from case to case. For a particular mode of action, 
certain observations may be established as essential in practice or 
policy, for example, measures of thyroid hormone levels in supporting 
thyroid

[[Page 17790]]

hormone elevation as a key event in carcinogenesis.
    Strength, consistency, specificity of association. A statistically 
significant association between events and a tumor response observed in 
well-conducted studies is generally supportive of causation. Consistent 
observations in a number of such studies with differing experimental 
designs increase that support, because different designs may reduce 
unknown biases. Studies showing ``recovery,'' i.e., absence or 
reduction of carcinogenicity when the event is blocked or diminished, 
are particularly useful tests of the association. Specificity of the 
association, without evidence of other modes of action, strengthens a 
causal conclusion. A lack of strength, consistency, and specificity of 
association weakens the causal conclusions for a particular mode of 
action.
     What is the level of statistical and biological 
significance for each event and for cancer?
     Do independent studies and different experimental 
hypothesis-testing approaches produce the same associations?
     Does the agent produce effects other than those 
hypothesized?
     Is the key event associated with precursor lesions?
    Pertinent observations include tumor response associated with 
events (site of action logically relates to event[s]), precursor 
lesions associated with events, initiation-promotion studies, and stop/
recovery studies.
    Dose-response concordance. If a key event and tumor endpoints 
increase with dose such that the key events forecast the appearance of 
tumors at a later time or higher dose, a causal association can be 
strengthened. Dose-response associations of the key event with other 
precursor events can add further strength. Difficulty arises when an 
event is not causal but accompanies the process generally. For example, 
if tumors and the hypothesized precursor both increase with dose, the 
two responses will be correlated regardless of whether a causal 
relationship exists. This is similar to the issue of confounding in 
epidemiologic studies. Dose-response studies coupled with mechanistic 
studies can assist in clarifying these relationships.
     What are the correlations among doses producing events and 
cancer?
    Pertinent observations include, but are not limited to, 2-year 
bioassay observation of lesions correlated with observations of hormone 
changes and the same lesions in shorter term studies or in interim 
sacrifice.
    Temporal relationship. If an event is shown to be causally linked 
to tumorigenesis, it will precede tumor appearance. An event may also 
be observed contemporaneously or after tumor appearance; these 
observations may add to the strength of association but not to the 
temporal association.
     What is the ordering of events that underlie the 
carcinogenic process?
     Is this ordering consistent among independent studies?
    Pertinent observations include studies of varying duration 
observing the temporal sequence of events and development of tumors.
    Biological plausibility and coherence. It is important that the 
hypothesized mode of action and the events that are part of it be based 
on contemporaneous understanding of the biology of cancer to be 
accepted. If the body of information under scrutiny is consistent with 
other examples (including structurally related agents) for which the 
hypothesized mode of action is accepted, the case is strengthened. 
Because some modes of action can be anticipated to evoke effects other 
than cancer, the available toxicity database on noncancer effects, for 
example, reproductive effects of certain hormonal disturbances, can 
contribute to this evaluation.
     Is the mode of action consistent with what is known about 
carcinogenesis in general and for the case specifically?
     Are carcinogenic effects and events consistent across 
structural analogues?
     Is the database on the agent internally consistent in 
supporting the purported mode of action, including relevant noncancer 
toxicities?
    Pertinent observations include the scientific basis for considering 
an hypothesized mode of action generally, given the contemporaneous 
state of knowledge of carcinogenic processes; previous examples of data 
sets showing the mode of action; data sets on analogues; and coherence 
of data in this case from cancer and noncancer toxicity studies.
2.4.3.3. Consideration of the Possibility of Other Modes of Action
    The possible involvement of more than one mode of action at the 
tumor site should be considered. Pertinent observations that are not 
consistent with the hypothesized mode of action can suggest the 
possibility of other modes of action. Some pertinent observations can 
be consistent with more than one mode of action. Furthermore, different 
modes of action can operate in different dose ranges; for example, an 
agent can act predominantly through cytotoxicity at high doses and 
through mutagenicity at lower doses where cytotoxicity may not occur.
    If there is evidence for more than one mode of action, each should 
receive a separate analysis. There may be an uneven level of 
experimental support for the different modes of action. Sometimes this 
can reflect disproportionate resources spent on investigating one 
particular mode of action and not the validity or relative importance 
of the other possible modes of action. Ultimately, however, the 
information on all of the modes of action should be integrated to 
better understand how and when each mode acts, and which mode(s) may be 
of interest for exposure levels relevant to human exposures of 
interest.
2.4.3.4. Conclusions About the Hypothesized Mode of Action
    Conclusions about the hypothesized mode of action should address 
the issues listed below. For those agents for which the mode of action 
is considered useful for the risk assessment, the weight of the 
evidence concerning mode of action in animals as well as its relevance 
for humans would be incorporated into the weight of evidence narrative 
(Section 2.5).
    (a) Is the hypothesized mode of action sufficiently supported in 
the test animals? Associations observed between key events and tumors 
may or may not support an inference of causation. The conclusion that 
the agent causes one or more key events that results in tumors is 
strengthened as more aspects of causation are satisfied and weakened as 
fewer are satisfied. Consistent results in different experiments that 
test the hypothesized mode of action build support for that mode of 
action. Replicating results in a similar experiment does not generally 
meaningfully strengthen the original evidence, and discordant results 
generally weaken that support. Experimental challenge to the 
hypothesized mode of action, where interrupting the sequence of key 
events suppresses the tumor response or enhancement of key events 
increases the tumor response, creates very strong support for the mode 
of action.
    (b) Is the hypothesized mode of action relevant to humans? If an 
hypothesized mode of action is sufficiently supported in the test 
animals, the sequence of key precursor events should be reviewed to 
identify critical similarities and differences between the test animals 
and humans. The question of concordance can be complicated by cross-
species differences in toxicokinetics or toxicodynamics. For example, 
the active

[[Page 17791]]

agent can be formed through different metabolic pathways in animals and 
humans. Any information suggesting quantitative differences between 
animals and humans is flagged for consideration in the dose-response 
assessment. This includes the potential for different internal doses of 
the active agent or for differential occurrence of a key precursor 
event.
    ``Relevance'' of a potential mode of action is considered in the 
context of characterization of hazard, not level of risk. Anticipated 
levels of human exposure are not used to determine whether the 
hypothesized mode of action is relevant to humans. Exposure information 
is integrated into the overall risk characterization.
    The question of relevance considers all populations and lifestages. 
It is possible that the conditions under which a mode of action 
operates exist primarily in a particular population or lifestage, for 
example, in those with a pre-existing hormonal imbalance. Other 
populations or lifestages may not be analogous to the test animals, in 
which case the question of relevance would be decided by inference.
    Special attention should be paid to whether tumors can arise from 
childhood exposure, considering various aspects of development during 
these lifestages. Because the studies that support a mode of action are 
typically conducted in mature animals, conclusions about relevance 
during childhood generally rely on inference. There is currently no 
standard Agency position regarding the issue of whether tumors arising 
through the hypothesized mode of action are relevant during childhood; 
understanding the mode of action implies that there are sufficient data 
(on either the specific agent or the general mode of action) to form a 
confident conclusion about relevance during childhood.
    (c) Which populations or lifestages can be particularly susceptible 
to the hypothesized mode of action? If an hypothesized mode of action 
is judged relevant to humans, information about the key precursor 
event(s) is reviewed to identify populations or lifestages that might 
reasonably expected to be particularly susceptible to their occurrence. 
Although agent-specific data would provide the strongest indication of 
susceptibility, this review may also rely on general knowledge about 
the precursor events and characteristics of individuals susceptible to 
these events. Any information suggesting quantitative differences 
between populations or lifestages should be flagged for consideration 
in the dose-response assessment (see Section 3.5). This includes the 
potential for a higher internal dose of the active agent or for an 
increased occurrence of a key precursor event. Quantitative differences 
may result in separate risk estimates for susceptible populations or 
lifestages.
    The possibility that childhood is a susceptible period for exposure 
should be explicitly addressed. Generic understanding of the mode of 
action can be used to gauge childhood susceptibility, and this 
determination can be refined through analysis of agent-specific data.
2.4.4. Evolution With Experience
    Several groups have proposed or incorporated mode of action into 
their risk assessments (see, e.g., U.S. EPA, 1991b; Sonich-Mullin et 
al., 2001; Meek et al., 2003). As the frameworks and mandates under 
which these evaluations were produced differ, the specific procedures 
described in and conclusions drawn may also differ. Nevertheless, the 
number of case studies from all venues remains limited. More experience 
with differing modes of action are expected to highlight and illustrate 
the strengths and limitations of the general framework proposed in 
these cancer guidelines. Moreover, additional toxicological techniques 
may expand or change scientific judgments regarding which information 
is useful for mode of action determinations. As warranted, additional 
guidance may be proposed as experience is gained and/or as 
toxicological knowledge advances.

2.5. Weight of Evidence Narrative

    The weight of evidence narrative is a short summary (one to two 
pages) that explains an agent's human carcinogenic potential and the 
conditions that characterize its expression. It should be sufficiently 
complete to be able to stand alone, highlighting the key issues and 
decisions that were the basis for the evaluation of the agent's 
potential hazard. It should be sufficiently clear and transparent to be 
useful to risk managers and non-expert readers. It may be useful to 
summarize all of the significant components and conclusions in the 
first paragraph of the narrative and to explain complex issues in more 
depth in the rest of the narrative.
    The weight of the evidence should be presented as a narrative 
laying out the complexity of information that is essential to 
understanding the hazard and its dependence on the quality, quantity, 
and type(s) of data available, as well as the circumstances of exposure 
or the traits of an exposed population that may be required for 
expression of cancer. For example, the narrative can clearly state to 
what extent the determination was based on data from human exposure, 
from animal experiments, from some combination of the two, or from 
other data. Similarly, information on mode of action can specify to 
what extent the data are from in vivo or in vitro exposures or based on 
similarities to other chemicals. The extent to which an agent's mode of 
action occurs only on reaching a minimum dose or a minimum duration 
should also be presented. A hazard might also be expressed 
disproportionately in individuals possessing a specific gene; such 
characterizations may follow from a better understanding of the human 
genome. Furthermore, route of exposure should be used to qualify a 
hazard if, for example, an agent is not absorbed by some routes. 
Similarly, a hazard can be attributable to exposures during a 
susceptible lifestage on the basis of our understanding of human 
development.
    The weight of evidence-of-evidence narrative should highlight:
     The quality and quantity of the data;
     All key decisions and the basis for these major decisions; 
and
     Any data, analyses, or assumptions that are unusual for or 
new to EPA.
    To capture this complexity, a weight of evidence narrative 
generally includes:
     Conclusions about human carcinogenic potential (choice of 
descriptor(s), described below),
     A summary of the key evidence supporting these conclusions 
(for each descriptor used), including information on the type(s) of 
data (human and/or animal, in vivo and/or in vitro) used to support the 
conclusion(s),
     Available information on the epidemiologic or experimental 
conditions that characterize expression of carcinogenicity (e.g., if 
carcinogenicity is possible only by one exposure route or only above a 
certain human exposure level),
     A summary of potential modes of action and how they 
reinforce the conclusions,
     Indications of any susceptible populations or lifestages, 
when available, and
     A summary of the key default options invoked when the 
available information is inconclusive.
    To provide some measure of clarity and consistency in an otherwise 
free-form narrative, the weight of evidence descriptors are included in 
the first sentence of the narrative. Choosing a descriptor is a matter 
of judgment and cannot be reduced to a formula. Each descriptor may be 
applicable to a wide

[[Page 17792]]

variety of potential data sets and weights of evidence. These 
descriptors and narratives are intended to permit sufficient 
flexibility to accommodate new scientific understanding and new testing 
methods as they are developed and accepted by the scientific community 
and the public. Descriptors represent points along a continuum of 
evidence; consequently, there are gradations and borderline cases that 
are clarified by the full narrative. Descriptors, as well as an 
introductory paragraph, are a short summary of the complete narrative 
that preserves the complexity that is an essential part of the hazard 
characterization. Users of these cancer guidelines and of the risk 
assessments that result from the use of these cancer guidelines should 
consider the entire range of information included in the narrative 
rather than focusing simply on the descriptor.
    In borderline cases, the narrative explains the case for choosing 
one descriptor and discusses the arguments for considering but not 
choosing another. For example, between ``suggestive'' and ``likely'' or 
between ``suggestive'' and ``inadequate,'' the explanation clearly 
communicates the information needed to consider appropriately the 
agent's carcinogenic potential in subsequent decisions.
    Multiple descriptors can be used for a single agent, for example, 
when carcinogenesis is dose-or route-dependent. For example, if an 
agent causes point-of-contact tumors by one exposure route but adequate 
testing is negative by another route, then the agent could be described 
as likely to be carcinogenic by the first route but not likely to be 
carcinogenic by the second. Another example is when the mode of action 
is sufficiently understood to conclude that a key event in tumor 
development would not occur below a certain dose range. In this case, 
the agent could be described as likely to be carcinogenic above a 
certain dose range but not likely to be carcinogenic below that range.
    Descriptors can be selected for an agent that has not been tested 
in a cancer bioassay if sufficient other information, e.g., 
toxicokinetic and mode of action information, is available to make a 
strong, convincing, and logical case through scientific inference. For 
example, if an agent is one of a well-defined class of agents that are 
understood to operate through a common mode of action and if that agent 
has the same mode of action, then in the narrative the untested agent 
would have the same descriptor as the class. Another example is when an 
untested agent's effects are understood to be caused by a human 
metabolite, in which case in the narrative the untested agent could 
have the same descriptor as the metabolite. As new testing methods are 
developed and used, assessments may increasingly be based on inferences 
from toxicokinetic and mode of action information in the absence of 
tumor studies in animals or humans.
    When a well-studied agent produces tumors only at a point of 
initial contact, the descriptor generally applies only to the exposure 
route producing tumors unless the mode of action is relevant to other 
routes. The rationale for this conclusion would be explained in the 
narrative.
    When tumors occur at a site other than the point of initial 
contact, the descriptor generally applies to all exposure routes that 
have not been adequately tested at sufficient doses. An exception 
occurs when there is convincing information, e.g., toxicokinetic data 
that absorption does not occur by another route.
    When the response differs qualitatively as well as quantitatively 
with dose, this information should be part of the characterization of 
the hazard. In some cases reaching a certain dose range can be a 
precondition for effects to occur, as when cancer is secondary to 
another toxic effect that appears only above a certain dose. In other 
cases exposure duration can be a precondition for hazard if effects 
occur only after exposure is sustained for a certain duration. These 
considerations differ from the issues of relative absorption or potency 
at different dose levels because they may represent a discontinuity in 
a dose-response function.
    When multiple bioassays are inconclusive, mode of action data are 
likely to hold the key to resolution of the more appropriate 
descriptor. When bioassays are few, further bioassays to replicate a 
study's results or to investigate the potential for effects in another 
sex, strain, or species may be useful.
    When there are few pertinent data, the descriptor makes a statement 
about the database, for example, ``Inadequate Information to Assess 
Carcinogenic Potential,'' or a database that provides ``Suggestive 
Evidence of Carcinogenic Potential.'' With more information, the 
descriptor expresses a conclusion about the agent's carcinogenic 
potential to humans. If the conclusion is positive, the agent could be 
described as ``Likely to Be Carcinogenic to Humans'' or, with strong 
evidence, ``Carcinogenic to Humans.'' If the conclusion is negative, 
the agent could be described as ``Not Likely to Be Carcinogenic to 
Humans.''
    Although the term ``likely'' can have a probabilistic connotation 
in other contexts, its use as a weight of evidence descriptor does not 
correspond to a quantifiable probability of whether the chemical is 
carcinogenic. This is because the data that support cancer assessments 
generally are not suitable for numerical calculations of the 
probability that an agent is a carcinogen. Other health agencies have 
expressed a comparable weight of evidence using terms such as 
``Reasonably Anticipated to Be a Human Carcinogen'' (NTP) or ``Probably 
Carcinogenic to Humans'' (International Agency for Research on Cancer).
    The following descriptors can be used as an introduction to the 
weight of evidence narrative. The examples presented in the discussion 
of the descriptors are illustrative. The examples are neither a 
checklist nor a limitation for the descriptor. The complete weight of 
evidence narrative, rather than the descriptor alone, provides the 
conclusions and the basis for them.
    ``Carcinogenic to Humans.'' This descriptor indicates strong 
evidence of human carcinogenicity. It covers different combinations of 
evidence.
     This descriptor is appropriate when there is convincing 
epidemiologic evidence of a causal association between human exposure 
and cancer.
     Exceptionally, this descriptor may be equally appropriate 
with a lesser weight of epidemiologic evidence that is strengthened by 
other lines of evidence. It can be used when all of the following 
conditions are met: (a) There is strong evidence of an association 
between human exposure and either cancer or the key precursor events of 
the agent's mode of action but not enough for a causal association, and 
(b) there is extensive evidence of carcinogenicity in animals, and (c) 
the mode(s) of carcinogenic action and associated key precursor events 
have been identified in animals, and (d) there is strong evidence that 
the key precursor events that precede the cancer response in animals 
are anticipated to occur in humans and progress to tumors, based on 
available biological information. In this case, the narrative includes 
a summary of both the experimental and epidemiologic information on 
mode of action and also an indication of the relative weight that each 
source of information carries, e.g., based on human information, based 
on limited human and extensive animal experiments.
    ``Likely to Be Carcinogenic to Humans.'' This descriptor is 
appropriate when the weight of the evidence is adequate to demonstrate 
carcinogenic

[[Page 17793]]

potential to humans but does not reach the weight of evidence for the 
descriptor ``Carcinogenic to Humans.'' Adequate evidence consistent 
with this descriptor covers a broad spectrum. As stated previously, the 
use of the term ``likely'' as a weight of evidence descriptor does not 
correspond to a quantifiable probability. The examples below are meant 
to represent the broad range of data combinations that are covered by 
this descriptor; they are illustrative and provide neither a checklist 
nor a limitation for the data that might support use of this 
descriptor. Moreover, additional information, e.g., on mode of action, 
might change the choice of descriptor for the illustrated examples. 
Supporting data for this descriptor may include:
     An agent demonstrating a plausible (but not definitively 
causal) association between human exposure and cancer, in most cases 
with some supporting biological, experimental evidence, though not 
necessarily carcinogenicity data from animal experiments;
     An agent that has tested positive in animal experiments in 
more than one species, sex, strain, site, or exposure route, with or 
without evidence of carcinogenicity in humans;
     A positive tumor study that raises additional biological 
concerns beyond that of a statistically significant result, for 
example, a high degree of malignancy, or an early age at onset;
     A rare animal tumor response in a single experiment that 
is assumed to be relevant to humans; or
     A positive tumor study that is strengthened by other lines 
of evidence, for example, either plausible (but not definitively 
causal) association between human exposure and cancer or evidence that 
the agent or an important metabolite causes events generally known to 
be associated with tumor formation (such as DNA reactivity or effects 
on cell growth control) likely to be related to the tumor response in 
this case.
    ``Suggestive Evidence of Carcinogenic Potential.'' This descriptor 
of the database is appropriate when the weight of evidence is 
suggestive of carcinogenicity; a concern for potential carcinogenic 
effects in humans is raised, but the data are judged not sufficient for 
a stronger conclusion. This descriptor covers a spectrum of evidence 
associated with varying levels of concern for carcinogenicity, ranging 
from a positive cancer result in the only study on an agent to a single 
positive cancer result in an extensive database that includes negative 
studies in other species. Depending on the extent of the database, 
additional studies may or may not provide further insights. Some 
examples include:
     A small, and possibly not statistically significant, 
increase in tumor incidence observed in a single animal or human study 
that does not reach the weight of evidence for the descriptor ``Likely 
to Be Carcinogenic to Humans.'' The study generally would not be 
contradicted by other studies of equal quality in the same population 
group or experimental system (see discussions of conflicting evidence 
and differing results, below);
     A small increase in a tumor with a high background rate in 
that sex and strain, when there is some but insufficient evidence that 
the observed tumors may be due to intrinsic factors that cause 
background tumors and not due to the agent being assessed. (When there 
is a high background rate of a specific tumor in animals of a 
particular sex and strain, then there may be biological factors 
operating independently of the agent being assessed that could be 
responsible for the development of the observed tumors.) In this case, 
the reasons for determining that the tumors are not due to the agent 
are explained;
     Evidence of a positive response in a study whose power, 
design, or conduct limits the ability to draw a confident conclusion 
(but does not make the study fatally flawed), but where the 
carcinogenic potential is strengthened by other lines of evidence (such 
as structure-activity relationships); or
     A statistically significant increase at one dose only, but 
no significant response at the other doses and no overall trend.
    ``Inadequate Information to Assess Carcinogenic Potential.'' This 
descriptor of the database is appropriate when available data are 
judged inadequate for applying one of the other descriptors. Additional 
studies generally would be expected to provide further insights. Some 
examples include:
     Little or no pertinent information;
     Conflicting evidence, that is, some studies provide 
evidence of carcinogenicity but other studies of equal quality in the 
same sex and strain are negative. Differing results, that is, positive 
results in some studies and negative results in one or more different 
experimental systems, do not constitute conflicting evidence, as the 
term is used here. Depending on the overall weight of evidence, 
differing results can be considered either suggestive evidence or 
likely evidence; or
     Negative results that are not sufficiently robust for the 
descriptor, ``Not Likely to Be Carcinogenic to Humans.''
    ``Not Likely to Be Carcinogenic to Humans.'' This descriptor is 
appropriate when the available data are considered robust for deciding 
that there is no basis for human hazard concern. In some instances, 
there can be positive results in experimental animals when there is 
strong, consistent evidence that each mode of action in experimental 
animals does not operate in humans. In other cases, there can be 
convincing evidence in both humans and animals that the agent is not 
carcinogenic. The judgment may be based on data such as:
     Animal evidence that demonstrates lack of carcinogenic 
effect in both sexes in well-designed and well-conducted studies in at 
least two appropriate animal species (in the absence of other animal or 
human data suggesting a potential for cancer effects),
     Convincing and extensive experimental evidence showing 
that the only carcinogenic effects observed in animals are not relevant 
to humans,
     Convincing evidence that carcinogenic effects are not 
likely by a particular exposure route (see Section 2.3), or
     Convincing evidence that carcinogenic effects are not 
likely below a defined dose range.
    A descriptor of ``not likely'' applies only to the circumstances 
supported by the data. For example, an agent may be ``Not Likely to Be 
Carcinogenic'' by one route but not necessarily by another. In those 
cases that have positive animal experiment(s) but the results are 
judged to be not relevant to humans, the narrative discusses why the 
results are not relevant.
    Multiple Descriptors. More than one descriptor can be used when an 
agent's effects differ by dose or exposure route. For example, an agent 
may be ``Carcinogenic to Humans'' by one exposure route but ``Not 
Likely to Be Carcinogenic'' by a route by which it is not absorbed. 
Also, an agent could be ``Likely to Be Carcinogenic'' above a specified 
dose but ``Not Likely to Be Carcinogenic'' below that dose because a 
key event in tumor formation does not occur below that dose.

2.6. Hazard Characterization

    The hazard characterization contains the hazard information needed 
for a full risk characterization (U.S. EPA, 2000b). It presents the 
results of the hazard assessment and explains how the weight of 
evidence conclusion was reached. The hazard characterization 
summarizes, in plain language, conclusions about the agent's potential 
effects, whether they can be expected to

[[Page 17794]]

depend qualitatively on the circumstances of exposure, and if anyone 
can be expected to be especially susceptible. It discusses the extent 
to which these conclusions are supported by data or are the result of 
default options invoked because the data are inconclusive. It explains 
how complex cases with differing results in different studies were 
resolved. The hazard characterization highlights the major issues 
addressed in the hazard assessment and discusses alternative 
interpretations of the data and the degree to which they are 
supportable scientifically and are consistent with EPA guidelines.
    When the conclusion is supported by mode of action information, the 
hazard characterization also provides a clear summary of the mode of 
action conclusions (see Section 2.4.3.4), including the completeness of 
the data, the strengths and limitations of the inferences made, the 
potential for other modes of action, and the implications of the mode 
of action for selecting viable approaches to the dose-response 
assessment. The hazard characterization also discusses the extent to 
which mode of action information is available to address the potential 
for disproportionate risks in specific populations or lifestages or the 
potential for enhanced risks on the basis of interactions with other 
agents or stressors, if anticipated.
    Topics that can be addressed in a hazard characterization include:
     Summary of the results of the hazard assessment;
     Identification of any likely susceptible populations and 
lifestages, especially attending to children, infants, and fetuses;
     Conclusions about the agent's mode of action, and 
implications for selecting approaches to the dose-response assessment;
     Identification of the available lines of evidence (e.g., 
animal bioassays, epidemiologic studies, toxicokinetic information, 
mode of action studies, and information about structural analogues or 
metabolites), highlighting data quality and coherence of results from 
different lines of evidence; and
     Strengths and limitations of the hazard assessment, 
highlighting significant issues in interpreting the data, alternative 
interpretations that are considered equally plausible, critical data 
gaps, and default options invoked when the available information is 
inconclusive.

3. Dose-Response Assessment

    Dose-response assessment estimates potential risks to humans at 
exposure levels of interest. Dose-response assessments are useful in 
many applications: Estimating risk at different exposure levels, 
estimating the risk reduction for different decision options, 
estimating the risk remaining after an action is taken, providing the 
risk information needed for benefit-cost analyses of different decision 
options, comparing risks across different agents or health effects, and 
setting research priorities. The purpose of the assessment should 
consider the quality of the data available, which will vary from case 
to case.
    A dose-response analysis is generally developed from each study 
that reports quantitative data on dose and response. Alternative 
measures of dose are available for analyzing human and animal studies 
(see Section 3.1). A two-step approach distinguishes analysis of the 
dose-response data from inferences made about lower doses. The first 
step is an analysis of dose and response in the range of observation of 
the experimental or epidemiologic studies (see Section 3.2). Modeling 
is encouraged to incorporate a wide range of experimental data into the 
dose-response assessment (see Sections 3.1.2, 3.2.1, 3.2.2, 3.2.3). The 
modeling yields a point of departure (POD) near the lower end of the 
observed range, without significant extrapolation to lower doses (see 
Sections 3.2.4, 3.2.5). The second step is extrapolation to lower doses 
(see Section 3.3). The extrapolation approach considers what is known 
about the agent's mode of action (see Section 3.3.1). Both linear and 
nonlinear approaches are available (see Sections 3.3.3, 3.3.4). When 
multiple estimates can be developed, the strengths and weaknesses of 
each are presented. In some cases, they may be combined in a way that 
best represents human cancer risk (see Section 3.3.5). Special 
consideration is given to describing dose-response differences 
attributable to different human exposure scenarios (see Section 3.4) 
and to susceptible populations and lifestages (see Section 3.5). It is 
important to discuss significant uncertainties encountered in the 
analysis (see Section 3.6) and to characterize other important aspects 
of the dose-response assessment (see Section 3.7).
    The scope, depth, and use of a dose-response assessment vary in 
different circumstances. Although the quality of dose-response data is 
not necessarily related to the weight of evidence descriptor, dose-
response assessments are generally completed for agents considered 
``Carcinogenic to Humans'' and ``Likely to Be Carcinogenic to Humans.'' 
When there is suggestive evidence, the Agency generally would not 
attempt a dose-response assessment, as the nature of the data generally 
would not support one; however, when the evidence includes a well-
conducted study, quantitative analyses may be useful for some purposes, 
for example, providing a sense of the magnitude and uncertainty of 
potential risks, ranking potential hazards, or setting research 
priorities. In each case, the rationale for the quantitative analysis 
is explained, considering the uncertainty in the data and the 
suggestive nature of the weight of evidence. These analyses generally 
would not be considered Agency consensus estimates. Dose-response 
assessments are generally not done when there is inadequate evidence, 
although calculating a bounding estimate from an epidemiologic or 
experimental study that does not show positive results can indicate the 
study's level of sensitivity and capacity to detect risk levels of 
concern.
    Cancer is a collection of several diseases that develop through 
cell and tissue changes over time. Dose-response assessment procedures 
based on tumor incidence have seldom taken into account the effects of 
key precursor events within the whole biological process due to lack of 
empirical data and understanding about these events. In this 
discussion, response data include measures of key precursor events 
considered integral to the carcinogenic process in addition to tumor 
incidence. These responses may include changes in DNA, chromosomes, or 
other key macromolecules; effects on growth signal transduction, 
including induction of hormonal changes; or physiological or toxic 
effects that include proliferative events diagnosed as precancerous but 
not pathology that is judged to be cancer. Analysis of such responses 
may be done along with that of tumor incidence to enhance the tumor 
dose-response analysis. If dose-response analysis of nontumor key 
events is more informative about the carcinogenic process for an agent, 
it can be used in lieu of, or in conjunction with, tumor incidence 
analysis for the overall dose-response assessment.
    As understanding of mode of action improves and new types of data 
become available, dose-response assessment will continue to evolve. 
These cancer guidelines encourage the development and application of 
new methods that improve dose-response assessment by reflecting new 
scientific understanding and new sources of information.

[[Page 17795]]

3.1. Analysis of Dose

    For each effect observed, dose-response assessment should begin by 
determining an appropriate dose metric. Several dose metrics have been 
used, e.g., delivered dose, body burden, and area under the curve, and 
others may be appropriate depending on the data and mode of action.
    Selection of an appropriate dose metric considers what data are 
available and what is known about the agent's mode of action at the 
target site, and uncertainties involved in estimation and application 
of alternative metrics. The dose metric specifies:
     The agent measured, preferably the active agent 
(administered agent or a metabolite);
     Proximity to the target site (exposure concentration, 
potential dose, internal dose, or delivered dose,\5\ reflecting 
increasing proximity); and
---------------------------------------------------------------------------

    \5\ Exposure is contact of an agent with the outer boundary of 
an organism. Exposure concentration is the concentration of a 
chemical in its transport or carrier medium at the point of contact. 
Dose is the amount of a substance available for interaction with 
metabolic processes or biologically significant receptors after 
crossing the outer boundary of an organism. Potential dose is the 
amount ingested, inhaled, or applied to the skin. Applied dose is 
the amount of a substance presented to an absorption barrier and 
available for absorption (although not necessarily having yet 
crossed the outer boundary of the organism). Absorbed dose is the 
amount crossing a specific absorption barrier (e.g., the exchange 
boundaries of skin, lung, and digestive tract) through uptake 
processes. Internal dose is a more general term, used without 
respect to specific absorption barriers or exchange boundaries. 
Delivered dose is the amount of the chemical available for 
interaction by any particular organ or cell (U.S. EPA, 1992a).
---------------------------------------------------------------------------

     The time component of the effective dose (cumulative dose, 
average dose, peak dose, or body burden).
    Analyses can be based on estimates of animal dose metrics or human 
dose metrics. The assessment should describe the approach used to 
select a dose metric and the reasons for this approach. The final 
analysis, however, should determine a human equivalent dose metric. 
This facilitates comparing results from different datasets and effects 
by using human equivalent dose/concentrations as common metrics. When 
appropriate, it may be necessary to convert dose metrics across 
exposure routes. When route-to-route extrapolations are made, the 
underlying data, algorithms, and assumptions are clearly described.
    Timing of exposure can also be important. When there is a 
susceptible lifestage, doses during the susceptible period are not 
equivalent to doses at other times, and they would be analyzed 
separately.
3.1.1. Standardizing Different Experimental Exposure Regimens
    Complex exposure or dosing regimens are often present in 
experimental and epidemiologic studies. The resulting internal dose 
depends on many variables, including concentration, duration, frequency 
of administration, and duration of recovery periods between 
administrations. Internal dose also depends on variables that are 
intrinsic to the exposed individual, such as lifestage and rates of 
metabolism and clearance. To facilitate comparing results from 
different study designs and to make inferences about human exposures, a 
summary estimate of the dose metric, whether the administered dose or 
inhalation exposure concentration or an internal metric, may be derived 
for a complex exposure regimen.
    Toxicokinetic modeling is the preferred approach for estimating 
dose metrics from exposure. Toxicokinetic models generally describe the 
relationship between exposure and measures of internal dose over time. 
More complex models can reflect sources of intrinsic variation, such as 
polymorphisms in metabolism and clearance rates. When a robust model is 
not available, or when the purpose of the assessment does not warrant 
developing a model, simpler approaches may be used.
    For chronic exposure studies, the cumulative exposure or dose 
administered often is expressed as an average over the duration of the 
study, as one consistent dose metric. This approach implies that a 
higher dose administered over a short duration is equivalent to a 
commensurately lower dose administered over a longer duration. 
Uncertainty usually increases as the duration becomes shorter relative 
to the averaging duration or the intermittent doses become more intense 
than the averaged dose. Moreover, doses during any specific susceptible 
or refractory period would not be equivalent to doses at other times. 
For these reasons, cumulative exposure or potential dose may be 
replaced by a more appropriate dose metric when indicated by the data.
    For mode of action studies, the dose metric should be calculated 
over a duration that reflects the time to occurrence of the key 
precursor effects. Mode of action studies are often of limited 
duration, as the precursors can be observed after less-than-chronic 
exposures. When the experimental exposure regimen is specified on a 
weekly basis (for example, 4 hours a day, 5 days a week), the daily 
exposure may be averaged over the week, where appropriate.
    Doses in studies at the cellular or molecular level can be 
difficult to relate to organ- or organism-level dose metrics. 
Toxicokinetic modeling can sometimes be used to relate doses at the 
cellular or molecular level to doses or exposures at higher levels of 
organization.
3.1.2. Toxicokinetic Data and Modeling
    In the absence of chemical-specific data, physiologically based 
toxicokinetic modeling is potentially the most comprehensive way to 
account for biological processes that determine internal dose. 
Physiologically based models commonly describe blood flow between 
physiological compartments and simulate the relationship between 
applied dose and internal dose. Toxicokinetic models generally need 
data on absorption, distribution, metabolism, and elimination of the 
administered agent and its metabolites.
    Additionally, in the case of inhalation exposures, models can 
explicitly characterize the geometry of the respiratory tract and the 
airflow through it, as well as the interaction of this airflow with the 
entrained particles or fibers and gases (Kimbell et al., 2001; 
Subramaniam et al., 2003). Because of large interspecies differences in 
airway morphometry such models can be particularly useful in 
interspecies extrapolations. When employed, however, the potential for 
large inter-individual differences in airway morphometry, are 
considered to ensure that the models provide information representative 
of human populations.
    Toxicokinetic models can improve dose-response assessment by 
revealing and describing nonlinear relationships between applied and 
internal dose. Nonlinearity observed in a dose-response curve often can 
be attributed to toxicokinetics (Hoel et al., 1983; Gaylor et al., 
1994), involving, for example, saturation or induction of enzymatic 
processes at high doses. In some cases, toxicokinetic processes tend to 
become linear at sufficiently low doses (Hattis, 1990).
    A discussion of confidence should accompany the presentation of 
model results and include consideration of model validation and 
sensitivity analysis, stressing the predictive performance of the model 
and whether the model is sufficient to support decision-making. 
Quantitative uncertainty analysis is important for evaluating the 
performance of a model, whether the model is based primarily on default 
assumptions or chemical-specific data. The uncertainty analysis covers 
questions of model uncertainty

[[Page 17796]]

(e.g., Is the model based on the appropriate biology and how does that 
affect estimates of dose metrics?) and parameter uncertainty (e.g., Do 
the data support unbiased and stable estimates of the model 
parameters?). When a delivered dose measure is used in animal-to-human 
extrapolation, the assessment discusses the confidence of the target 
tissue and its toxicodynamics being the same in both species (see 
Section 3.6). Toxicokinetic modeling results may be presented alone as 
the preferred method of estimating human equivalent exposures or doses, 
or these results may be presented in parallel with default procedures 
(see Section 3.1.3), depending on the confidence in the modeling.
3.1.3. Cross-Species Scaling Procedures
    Standard cross-species scaling procedures are available when the 
data are not sufficient to support a toxicokinetic model or when the 
purpose of the assessment does not warrant developing one. The aim is 
to define exposure levels for humans and animals that are expected to 
produce the same degree of effect (U.S. EPA, 1992b), taking into 
account differences in scale between test animals and humans, such as 
size and lifespan.
3.1.3.1. Oral Exposures
    For oral exposures, administered doses should be scaled from 
animals to humans on the basis of equivalence of mg/kg3/4-d 
(milligrams of the agent normalized by the \3/4\ power of body weight 
per day) (U.S. EPA, 1992b). The \3/4\ power is consistent with current 
science, including empirical data that allow comparison of potencies in 
humans and animals, and it is also supported by analysis of the 
allometric variation of key physiological parameters across mammalian 
species. It is generally more appropriate at low doses, where sources 
of nonlinearity such as saturation of enzyme activity are less likely 
to occur. This scaling is intended as an unbiased estimate rather than 
a conservative one. Equating exposure concentrations in food or water 
is an alternative version of the same approach, because daily intakes 
of food or water are approximately proportional to the \3/4\ power of 
body weight.
    The aim of these cross-species scaling procedures is to estimate 
administered doses in animals and humans that result in equal lifetime 
risks. It is useful to recognize two components of this equivalence: 
toxicokinetic equivalence, which determines administered doses in 
animals and humans that yield equal tissue doses, and toxicodynamic 
equivalence, which determines tissue doses in animals and humans that 
yield equal lifetime risks (U.S. EPA, 1992b). Toxicokinetic modeling 
(see Section 3.1.2) addresses factors associated with toxicokinetic 
equivalence, and toxicodynamic modeling (see Section 3.2.2) addresses 
factors associated with toxicodynamic equivalence. When toxicokinetic 
modeling is used without toxicodynamic modeling, the dose-response 
assessment develops and supports an approach for addressing 
toxicodynamic equivalence, perhaps by retaining some of the cross-
species scaling factor (e.g., using the square root of the cross-
species scaling factor or using a factor of 3 to cover toxicodynamic 
differences between animals and humans, as is currently done in 
deriving inhalation reference concentrations [U.S. EPA, 1994]).
    When assessing risks from childhood exposure, the mg/
kg3/4-d scaling factor does not use the child's body weight 
(U.S. EPA, 1992b). This reflects several uncertainties in extrapolating 
risks to children:
     The data supporting the mg/kg3/4-d scaling 
factor were derived for differences across species and may not apply as 
well to differently sized individuals of the same species or to 
different lifestages.
     In addition to metabolic differences, there are also 
important toxicodynamic differences; for example, children have faster 
rates of cell division than do adults, so scaling across different 
lifestages and species simultaneously may be particularly uncertain.
3.1.3.2. Inhalation Exposures
    For inhalation exposures experimental exposure concentrations are 
replaced with human equivalent concentrations calculated using EPA's 
methods for deriving inhalation reference concentrations (U.S. EPA, 
1994), which give preference to the use of toxicokinetic modeling. When 
toxicokinetic models are unavailable, default dosimetry models are 
employed to extrapolate from experimental exposure concentrations to 
human equivalent concentrations. When toxicokinetic modeling or 
dosimetry modeling is used without toxicodynamic modeling, the dose-
response assessment develops and supports an approach for addressing 
toxicodynamic equivalence.
    The default dosimetry models typically involve the use of species-
specific physiologic and anatomic factors relevant to the form of the 
agent (e.g., particle or gas) and categorized with regard to whether 
the response occurs either locally (i.e., within the respiratory tract) 
or remotely. For example, current default models (U.S. EPA, 1994) use 
parameters such as:
     Inhalation rate and surface area of the affected part of 
the respiratory tract for gases eliciting the response locally,
     Blood:gas partition coefficients for remote acting gases,
     Fractional deposition with inhalation rate and surface 
area of the affected part of the respiratory tract for particles 
eliciting the response locally, and
     Fractional deposition with inhalation rate and body weight 
for particles eliciting the response remotely.
    The current default values for some parameters used in the default 
models (e.g., breathing rate and respiratory tract surface area) are 
based on data from adults (U.S. EPA, 1994). The human respiratory 
system passes through several distinct stages of maturation and growth 
during the first several years of life and into adolescence (Pinkerton 
and Joad, 2000), during which characteristics important to disposition 
of inhaled toxicants may vary. Children and adults breathing the same 
concentration of an agent may receive different doses to the body or 
lungs (U.S. EPA, 2002b). Consequently, it may be appropriate to 
evaluate the default models by considering physiologic and anatomic 
factors representative of early lifestages, for example through the 
substitution of child-specific parameters (U.S. EPA, 2002b). Such 
evaluation uses the default model and dosimetric adjustment in use at 
the time of the assessment coupled with the best understanding of 
child-specific parameters at that time (e.g., drawn from the scientific 
literature). This analysis is undertaken with caution: (1) because of 
the correlations between activity level, breathing rate, respiratory 
tract dimensions, and body weight and (2) to avoid the possibility of 
mismatching the type of agent (gas or particle) and its site of 
response (within the respiratory tract or remote from the respiratory 
tract) with the relevant dosimetry factors in use at the time of the 
assessment. Analyses of children's inhalation dosimetry are also 
considered when using model structures beyond the default models (e.g., 
physiologically based toxicokinetic models).
    When using dosimetry modeling, the comparison of human-equivalent 
concentrations for different lifestages (e.g., for an adult and a 
child) can indicate whether it is important to carry both 
concentrations forward in the dose-response assessment or whether a 
verbal characterization of any findings will suffice.

[[Page 17797]]

3.1.4. Route Extrapolation
    In certain situations, an assessment based on studies of one 
exposure route may be applied to another exposure route. Route-to-route 
extrapolation has both qualitative and quantitative aspects. For the 
qualitative aspect, the assessor should weigh the degree to which 
positive results by one exposure route support a judgment that similar 
results would be expected by another route. In general, confidence in 
making such a judgment is strengthened when tumors are observed at a 
site distant from the portal of entry and when absorption is similar 
through both routes. In the absence of contrary data, a qualitative 
default option can be used: If the agent is absorbed through an 
exposure route to give an internal dose, it may be carcinogenic by that 
route.
    When a qualitative extrapolation can be supported, quantitative 
extrapolation may still be problematic due to the absence of adequate 
data. The differences in biological processes among routes of exposure 
(oral, inhalation, dermal) can be great because of, for example, first-
pass effects and different results from different exposure patterns. 
There is no generally applicable method for accounting for these 
differences in uptake processes in a quantitative route-to-route 
extrapolation of dose-response data in the absence of good data on the 
agent of interest. Therefore, route-to-route extrapolation of dose data 
relies on a case-by-case analysis of available data. When good data on 
the agent itself are limited, an extrapolation analysis can be based on 
expectations from physical and chemical properties of the agent, 
properties and route-specific data on structurally analogous compounds, 
or in vitro or in vivo uptake data on the agent.
    Route-to-route uptake models may be applied if model parameters are 
suitable for the compound of interest. Such models are currently 
considered interim methods; further model development and validation is 
awaiting the development of more extensive data. For screening or 
hazard ranking, route-to-route extrapolation may be based on assumed 
quantitative comparability as a default, as long as it is reasonable to 
assume absorption by compared routes. When route-to-route extrapolation 
is used, the assessor's degree of confidence in both the qualitative 
and quantitative extrapolation is discussed in the assessment and 
highlighted in the dose-response characterization.
    Toxicokinetic modeling can be used to compare results of studies by 
different exposure routes. Results can also be compared on the basis of 
internal dose for effects distant from the point of contact.
    Route extrapolation can be used to understand how internal dose and 
subsequent effects depend on exposure route. If testing by different 
exposure routes is available, the observation of similar or dissimilar 
internal doses can be important in determining whether and what 
conclusions can be made concerning the dose-response function(s) for 
different routes of exposure.

3.2. Analysis in the Range of Observation

    The principle underlying these cancer guidelines is to use 
approaches that include as much information as possible. Quantitative 
information about key precursor events can be used to develop a 
toxicodynamic model. Alternatively, such information can be fitted by 
empirical models to extend the dose-response analysis of tumor 
incidence to lower doses and response levels. The analysis in the range 
of observation is used to establish a POD near the lower end of the 
observed range (see Section 3.3).
3.2.1. Epidemiologic Studies
    Ideally, epidemiologic data would be used to select the dose-
response function for human exposures. Because epidemiologic data are 
usually limited and many models may fit the data (Samet et al.,1998), 
other factors may influence model choice. For epidemiologic studies, 
including those with grouped data, analysis by linear models in the 
range of observation is generally appropriate unless the fit is poor. 
The relatively small exposure range observed in many epidemiologic 
studies, for example, makes it difficult to discern the shape of the 
exposure-or dose-response curve. Exposure misclassification and errors 
in exposure estimation also obscure the shape of the dose-response 
curve. When these errors are unsystematic or random, the result is 
frequently to bias the risk estimates toward zero. When a linear model 
fits poorly, more flexible models that allow for low-dose linearity, 
for example, a linear-quadratic model or a Hill model (Murrell et al., 
1998), are often considered next.
    Analysis of epidemiologic studies depends on the type of study and 
quality of the data, particularly the availability of quantitative 
measures of exposure. The objective is to develop a dose-response curve 
that estimates the incidence of cancer attributable to the dose (as 
estimated from the exposure) to the agent. In some cases, e.g., tobacco 
smoke or occupational exposures, the data are in the range of the 
exposures of interest. In other cases, as with data from animal 
experiments, information from the observable range is extrapolated to 
exposures of interest.
    Analysis of effects raises additional issues:
     Many studies collect information from death certificates, 
which leads to estimates of mortality rather than incidence. Because 
survival rates vary for different cancers, the analysis may be improved 
by adjusting mortality figures to reflect the relationship between 
incidence and mortality.
     Epidemiologic studies, by their nature, are limited in the 
extent to which they can control for effects due to exposures from 
other agents. In some cases, the agent can have discernible interactive 
effects with another agent, making it possible to estimate the 
contribution of each agent as a risk factor for the effects of the 
other. For example, competing risks in a study population can limit the 
observed occurrence of cancer, while additive effects may lead to an 
increase occurrence of cancer. In the case of rates not already so 
adjusted, the analysis can be improved by correcting for competing or 
additive risks that are not similar in exposed and comparison groups.
     Comparison groups that are not free from exposure to the 
agent can bias the risk estimates toward zero. The analysis can be 
improved by considering background exposures in the exposed and 
comparison groups.
     The latent period for most cancers implies that exposures 
immediately preceding the detection of a tumor would be less likely to 
have contributed to its development and, therefore, may count less in 
the analysis. Study subjects who were first exposed near the end of the 
study may not have had adequate time since exposure for cancer to 
develop; therefore, analysis of their data may be similar to analysis 
of data for those who were not exposed. However, for carcinogens that 
act on multiple stages of the carcinogenic process, especially the 
later stages, all periods of exposure. including recent exposures, may 
be important.
    Some study designs can yield only a partial characterization of the 
overall hazard and therefore risk as, for example, in studies that: (1) 
investigate only one effect (typical of many case-control studies), (2) 
include only one population segment (e.g., male workers or workers of 
one socioeconomic class), or (3) include only one lifestage (e.g., 
childhood leukemia following maternal exposure to contaminated drinking 
water). To obtain a more complete

[[Page 17798]]

characterization that includes risks of other cancers, estimates from 
these studies can be supplemented with estimates from other studies 
that investigated other cancers, population segments, or lifestages 
(see Section 3.5).
    When several studies are available for dose-response analysis, 
meta-analysis can provide a systematic approach to weighing positive 
studies and those studies that do not show positive results, and 
calculating an overall risk estimate with greater precision. Issues 
considered include the comparability of studies, heterogeneity across 
studies, and the potential for a single large study to dominate the 
analysis. Confidence in a meta-analysis is increased when it considers 
study quality, including definition of the study population and 
comparison group, measurement of exposure, potential for exposure 
misclassification, adequacy of follow-up period, and analysis of 
confounders (see Section 2.2.1.3).
3.2.2. Toxicodynamic (``Biologically Based'') Modeling
    Toxicodynamic modeling can be used when there are sufficient data 
to ascertain the mode of action (see Section 2.4) and quantitatively 
support model parameters that represent rates and other quantities 
associated with the key precursor events of the mode of action. 
Toxicodynamic modeling is potentially the most comprehensive way to 
account for the biological processes involved in a response. Such 
models seek to reflect the sequence of key precursor events that lead 
to cancer. Toxicodynamic models can contribute to dose-response 
assessment by revealing and describing nonlinear relationships between 
internal dose and cancer response. Such models may provide a useful 
approach for analysis in the range of observation, provided the purpose 
of the assessment justifies the effort involved.
    If a new model is developed for a specific agent, extensive data on 
the agent are important for identifying the form of the model, 
estimating its parameters, and building confidence in its results. 
Conformance to the observed tumor incidence data alone does not 
establish a model's validity, as a model can be designed with a 
sufficiently large number of parameters so as to fit any given dataset. 
Peer review, including both an examination of the scientific basis 
supporting the model and an independent evaluation of the model's 
performance, is an essential part of evaluating the new model.
    If a standard model already exists for the agent's mode of action, 
the model can be adapted for the agent by using agent-specific data to 
estimate the model's parameters. An example is the two-stage clonal 
expansion model developed by Moolgavkar and Knudson (1981) and Chen and 
Farland (1991). These models continue to be improved as more 
information becomes available.
    It is possible for different models to provide equivalent fits to 
the observed data but to diverge substantially in their projections at 
lower doses. When model parameters are estimated from tumor incidence 
data, it is often the case that different combinations of parameter 
estimates can yield similar results in the observed range. For this 
reason, critical parameters (e.g., mutation rates and cell birth and 
death rates) are estimated from laboratory studies and not by curve-
fitting to tumor incidence data (Portier, 1987). This approach reduces 
model uncertainty (see Section 3.6) and ensures that the model does not 
give answers that are biologically unrealistic. This approach also 
provides a robustness of results, where the results are not likely to 
change substantially if fitted to slightly different data.
    Toxicodynamic modeling can provide insight into the relationship 
between tumors and key precursor events. For example, a model that 
includes cell proliferation can be used to explore the extent to which 
small increases in the cell proliferation rate can lead to large 
lifetime tumor incidences (Gaylor and Zheng, 1996). In this way, 
toxicodynamic modeling can be used to select and characterize an 
appropriate precursor response level (see Section 3.2.2, 3.2.5).
3.2.3. Empirical Modeling (``Curve Fitting'')
    When a toxicodynamic model is not available or when the purpose of 
the assessment does not warrant developing such a model, empirical 
modeling (sometimes called ``curve fitting'') should be used in the 
range of observation. A model can be fitted to data on either tumor 
incidence or a key precursor event. Goodness-of-fit to the experimental 
observations is not by itself an effective means of discriminating 
among models that adequately fit the data (OSTP, 1985). Many different 
curve-fitting models have been developed, and those that fit the 
observed data reasonably well may lead to several-fold differences in 
estimated risk at the lower end of the observed range. Another problem 
occurs when a multitude of alternatives are presented without 
sufficient context to make a reasoned judgment about the alternatives. 
This form of model uncertainty reflects primarily the availability of 
different computer models and not biological information about the 
agent being assessed or about carcinogenesis in general. In cases where 
curve-fitting models are used because the data are not adequate to 
support a toxicodynamic model, there generally would be no biological 
basis to choose among alternative curve-fitting models. However, in 
situations where there are alternative models with significant 
biological support, the decisionmaker can be informed by the 
presentation of these alternatives along with their strengths and 
uncertainties.
    Quantitative data on precursors can be used in conjunction with, or 
in lieu of, data on tumor incidence to extend the dose-response curve 
to lower doses. Caution is used with rates of molecular events such as 
mutation or cell proliferation or signal transduction. Such rates can 
be difficult to relate to cell or tissue changes overall. The timing of 
observations of these phenomena, as well as the cell type involved, is 
linked to other precursor events to ensure that the measurement is 
truly a key event (Section 2.4).
    For incidence data on either tumors or a precursor, an established 
empirical procedure is used to provide objectivity and consistency 
among assessments. The procedure models incidence, corrected for 
background, as an increasing function of dose. The models are 
sufficiently flexible in the observed range to fit linear and nonlinear 
datasets. Additional judgments and perhaps alternative analyses are 
used when the procedure fails to yield reliable results. For example, 
when a model's fit is poor, the highest dose is often omitted in cases 
where it is judged that the highest dose reflects competing toxicity 
that is more relevant at high doses than at lower doses. Another 
example is when there are large differences in survival across dose 
groups; here, models that includes time-to-tumor or time-to-event 
information may be useful.
    For continuous data on key precursor effects, empirical models can 
be chosen on the basis of the structure of the data. The rationale for 
the choice of model, the alternatives considered and rejected, and a 
discussion of model uncertainty are included in the dose-response 
characterization.
3.2.4. Point of Departure (POD)
    For each tumor response, a POD from the observed data should be 
estimated to mark the beginning of extrapolation to lower doses. The 
POD is an estimated dose (expressed in human-equivalent terms) near the 
lower end of the observed range without significant extrapolation to 
lower doses.

[[Page 17799]]

    The POD is used as the starting point for subsequent extrapolations 
and analyses. For linear extrapolation, the POD is used to calculate a 
slope factor (see Section 3.3.3), and for nonlinear extrapolation the 
POD is used in the calculation of a reference dose or reference 
concentration (see Section 3.3.4). In a risk characterization, the POD 
is part of the determination of a margin of exposure (see Section 5.4). 
With appropriate adjustments, it can also be used as the basis for 
hazard rankings that compare different agents or health effects.
    The lowest POD is used that is adequately supported by the data. If 
the POD is above some data points, it can fail to reflect the shape of 
the dose-response curve at the lowest doses and can introduce bias into 
subsequent extrapolations (see Figure 3-1). On the other hand, if the 
POD is far below all observed data points, it can introduce model 
uncertainty and parameter uncertainty (see Section 3.6) that increase 
with the distance between the data and the POD. Use of a POD at the 
lowest level supported by the data seeks to balance these 
considerations. It uses information from the model(s) a small distance 
below the observed range rather than discarding this information and 
using extrapolation procedures in a range where the model(s) can 
provide some useful information. Statistical tests involving the ratio 
of the central estimate and its lower bound (i.e., EDxx/
LEDxx) can be useful for evaluating how well the data 
support a model's estimates at a particular response level. (Note that 
the ability to model at a particular response level is not the same as 
the study's ability to identify an increase at that response level as 
statistically significant.)
    The POD for extrapolating the relationship to environmental 
exposure levels of interest, when the latter are outside the range of 
observed data, is generally the lower 95% confidence limit on the 
lowest dose level that can be supported for modeling by the data. SAB 
(1997) suggested that, ``it may be appropriate to emphasize lower 
statistical bounds in screening analyses and in activities designed to 
develop an appropriate human exposure value, since such activities 
require accounting for various types of uncertainties and a lower bound 
on the central estimate is a scientifically-based approach accounting 
for the uncertainty in the true value of the ED10 [or 
central estimate].'' However, the consensus of the SAB (1997) was that, 
``both point estimates and statistical bounds can be useful in 
different circumstances, and recommended that the Agency routinely 
calculate and present the point estimate of the ED10 [or 
central estimate] and the corresponding upper and lower 95% statistical 
bounds.'' For example, it may be appropriate to emphasize the central 
estimate in activities that involve formal uncertainty analysis that 
are required by OMB Circular A-4 (OMB, 2003) as well as ranking agents 
as to their carcinogenic hazard. Thus, risk assessors should calculate, 
to the extent practicable, and present the central estimate and the 
corresponding upper and lower statistical bounds (such as confidence 
limits) to inform decisionmakers.
    When tumor data are used, a POD is obtained from the modeled tumor 
incidences. Conventional cancer bioassays, with approximately 50 
animals per group, generally can support modeling down to an increased 
incidence of 1-10%; epidemiologic studies, with larger sample sizes, 
below 1%. Various models commonly used for carcinogens yield similar 
estimates of the POD at response levels as low as 1% (Krewski and Van 
Ryzin, 1981; Gaylor et al., 1994). Consequently, response levels at or 
below 10% can often be used as the POD. As a modeling convention, the 
lower bound on the doses associated with standard response levels of 1, 
5, and 10% can be analyzed, presented, and considered. For making 
comparisons at doses within the observed range, the ED10 and 
LED10 are also reported and can be used, with appropriate 
adjustments, in hazard rankings that compare different agents or health 
effects (U.S. EPA, 2002c). A no-observed-adverse-effect level (NOAEL) 
generally is not used for assessing the potential for carcinogenic 
response when one or more models can be fitted to the data.
    When good quality precursor data are available and are clearly tied 
to the mode of action of the compound of interest, models that include 
both tumors and their precursors may be advantageous for deriving a 
POD. Such models can provide insight into quantitative relationships 
between tumors and precursors (see Section 3.2.2), possibly suggesting 
the precursor response level that is associated with a particular tumor 
response level. The goal is to use precursor data to extend the 
observed range below what can be observed in tumor studies. EPA is 
continuing to examine this issue and anticipates that findings and 
conclusions may result in supplemental guidance to these cancer 
guidelines. If the precursor data are drawn from small samples or if 
the quantitative relationship between tumors and precursors is not well 
defined, then the tumor data will provide a more reliable POD. 
Precursor effects may or may not be biologically adverse in themselves; 
the intent is to consider not only tumors but also damage that can lead 
to subsequent tumor development by the agent. Analysis of continuous 
data may differ from discrete data; Murrell et al. (1998) discuss 
alternative approaches to deriving a POD from continuous data.
3.2.5. Characterizing the POD: The POD Narrative
    As a single-point summary of a single dose-response curve, the POD 
alone does not convey all the critical information present in the data 
from which it is derived. To convey a measure of uncertainty, the POD 
should be presented as a central estimate with upper and lower bounds. 
A POD narrative summarizes other important features of the database and 
the POD that are important to account for in low-dose extrapolations or 
other analyses.
    (a) Nature of the response. Is the POD based on tumors or a 
precursor? If on tumors, does the POD measure incidence or mortality? 
Is it a lifetime measure or was the study terminated early? The 
relationships between precursors and tumors, incidence and mortality, 
and lifetime and early-termination results vary from case to case. 
Modeling can provide quantitative insight into these relationships, for 
example, linking a change in a precursor response to a tumor incidence 
(see Section 3.2.2). This can aid in evaluating the significance of the 
response at the POD and adjusting different PODs to make them 
comparable.
    (b) Level of the response. What level of response is associated 
with the POD, for example, 1% cancer risk, 10% cancer risk, or 10% 
change in a precursor measure?
    (c) Nature of the study population. Is the POD based on humans or 
animals? How large is the effective sample size? Is the study group 
representative of the general population, of healthy adult workers, or 
of a susceptible group? Are both sexes represented? Did exposure occur 
during a susceptible lifestage?
    (d) Slope of the dose-response curve at the POD. How does response 
change as dose is reduced below the POD? A steep slope indicates that 
risk decreases rapidly as dose decreases. On the other hand, a steep 
slope also indicates that errors in an exposure assessment can lead to 
large errors in estimating risk. Both aspects of the slope are 
important. The slope also indicates whether dose-response curves for 
different effects are likely to cross below the POD. For example, in 
the ED01 study where 2-

[[Page 17800]]

acetylaminofluorene caused bladder carcinomas and liver carcinomas in 
mice (Littlefield et al., 1980), the dose-response curves for these 
tumors cross between 10% and 1% response (see Figure 3-2). This 
crossing, which can be inferred from the slopes of the curves at a 10% 
response, shows how considering the slope can lead to better inferences 
about the predominant effects expected at lower doses. Mode of action 
data can also be useful; quantitative information about key precursor 
events can be used to describe how risk decreases as dose decreases 
below the POD.
    (e) Relationship of the POD with other cancers. How does the POD 
for this cancer relate to PODs for other cancers observed in the 
database? For example, a POD based on male workers would not reflect 
the implications of mammary tumors in female rats or mice.
    (f) Extent of the overall cancer database. Have potential cancer 
responses been adequately studied (e.g., were all tissues examined), or 
is the database limited to particular effects, population segments, or 
lifestages? Do the mode of action data suggest a potential for cancers 
not observed in the database (e.g., disruption of particular endocrine 
pathways leading to related cancers)?
3.2.6. Relative Potency Factors
    Relative potency factors (of which toxicity equivalence factors are 
a special case) can be used for a well-defined class of agents that 
operate through a common mode of action for the same toxic endpoint. A 
complete dose-response assessment is conducted for one well-studied 
member of the class that serves as the index chemical for the class. 
The other members of the class are tied to the index chemical by 
relative potency factors that are based on characteristics such as 
relative toxicological outcomes, relative metabolic rates, relative 
absorption rates, quantitative SARs, or receptor binding 
characteristics (U.S. EPA, 2000c). Examples of this approach are the 
toxicity equivalence factors for dioxin-like compounds and the relative 
potency factors for some carcinogenic polycyclic aromatic hydrocarbons. 
Whenever practicable, toxicity equivalence factors should be validated 
and accompanied by quantitative uncertainty analysis.

3.3. Extrapolation to Lower Doses

    The purpose of low-dose extrapolation is to provide as much 
information as possible about risk in the range of doses below the 
observed data. The most versatile forms of low-dose extrapolation are 
dose-response models that characterize risk as a probability over a 
range of environmental exposure levels. These risk probabilities allow 
estimates of the risk reduction under different decision options and 
estimates of the risk remaining after an action is taken and provide 
the risk information needed for benefit-cost analyses of different 
decision options.
    When a dose-response model is not developed for lower doses, 
another form of low-dose extrapolation is a safety assessment that 
characterizes the safety of one lower dose, with no explicit 
characterization of risks above or below that dose. Although this type 
of extrapolation may be adequate for evaluation of some decision 
options, it may not be adequate for other purposes (e.g., benefit-cost 
analyses) that require a quantitative characterization of risks across 
a range of doses. At this time, safety assessment is the default 
approach for tumors that arise through a nonlinear mode of action; 
however, EPA continues to explore methods for quantifying dose-response 
relationships over a range of environmental exposure levels for tumors 
that arise through a nonlinear mode of action (U.S. EPA, 2002c). EPA 
program offices that need this more explicit dose-response information 
may develop and apply methods that are informed by the methods 
described in these cancer guidelines.
3.3.1. Choosing an Extrapolation Approach
    The approach for extrapolation below the observed data considers 
the understanding of the agent's mode of action at each tumor site (see 
Section 2.4). Mode of action information can suggest the likely shape 
of the dose-response curve at lower doses. The extent of inter-
individual variation is also considered, with greater variation 
spreading the response over a wider range of doses.
    Linear extrapolation should be used when there are MOA data to 
indicate that the dose-response curve is expected to have a linear 
component below the POD. Agents that are generally considered to be 
linear in this region include:
     Agents that are DNA-reactive and have direct mutagenic 
activity, or
     Agents for which human exposures or body burdens are high 
and near doses associated with key precursor events in the carcinogenic 
process, so that background exposures to this and other agents 
operating through a common mode of action are in the increasing, 
approximately linear, portion of the dose-response curve.
    When the weight of evidence evaluation of all available data are 
insufficient to establish the mode of action for a tumor site and when 
scientifically plausible based on the available data, linear 
extrapolation is used as a default approach, because linear 
extrapolation generally is considered to be a health-protective 
approach. Nonlinear approaches generally should not be used in cases 
where the mode of action has not been ascertained. Where alternative 
approaches with significant biological support are available for the 
same tumor response and no scientific consensus favors a single 
approach, an assessment may present results based on more than one 
approach.
    A nonlinear approach should be selected when there are sufficient 
data to ascertain the mode of action and conclude that it is not linear 
at low doses and the agent does not demonstrate mutagenic or other 
activity consistent with linearity at low doses. Special attention is 
important when the data support a nonlinear mode of action but there is 
also a suggestion of mutagenicity. Depending on the strength of the 
suggestion of mutagenicity, the assessment may justify a conclusion 
that mutagenicity is not operative at low doses and focus on a 
nonlinear approach, or alternatively, the assessment may use both 
linear and nonlinear approaches.
    Both linear and nonlinear approaches may be used when there are 
multiple modes of action. If there are multiple tumor sites, one with a 
linear and another with a nonlinear mode of action, then the 
corresponding approach is used at each site. If there are multiple 
modes of action at a single tumor site, one linear and another 
nonlinear, then both approaches are used to decouple and consider the 
respective contributions of each mode of action in different dose 
ranges. For example, an agent can act predominantly through 
cytotoxicity at high doses and through mutagenicity at lower doses 
where cytotoxicity does not occur. Modeling to a low response level can 
be useful for estimating the response at doses where the high-dose mode 
of action would be less important.
3.3.2. Extrapolation Using a Toxicodynamic Model
    The preferred approach is to develop a toxicodynamic model of the 
agent's mode of action and use that model for extrapolation to lower 
doses (see Section 3.2.2). The extent of extrapolation is governed by 
an analysis of model uncertainty, where alternative models that fit 
similarly in the observed

[[Page 17801]]

range can diverge below that range (see Section 3.6). Substantial 
divergence is likely when model parameters are estimated from tumor 
incidence data, so that different combinations of parameter estimates 
yield similar fits in the observed range but have different 
implications at lower doses. An analysis of model uncertainty can be 
used to determine the range where extrapolation using the toxicodynamic 
model is supported and where further extrapolation would be based on 
either a linear or a nonlinear default, as appropriate (see Sections 
3.3.3, 3.3.4).
3.3.3. Extrapolation Using a Low-Dose, Linear Model
    Linear extrapolation should be used in two distinct circumstances: 
(1) When there are data to indicate that the dose-response curve has a 
linear component below the POD, or (2) as a default for a tumor site 
where the mode of action is not established (see Section 3.3.1). For 
linear extrapolation, a line should be drawn from the POD to the 
origin, corrected for background. This implies a proportional (linear) 
relationship between risk and dose at low doses. (Note that the dose-
response curve generally is not linear at higher doses.)
    The slope of this line, known as the slope factor, is an upper-
bound estimate of risk per increment of dose that can be used to 
estimate risk probabilities for different exposure levels. The slope 
factor is equal to 0.01/LED01 if the LED01 is 
used as the POD.
    Unit risk estimates express the slope in terms of [mu]g/L drinking 
water or [mu]g/m3 or ppm air. In general, the drinking water 
unit risk is derived by converting a slope factor from units of mg/kg-d 
to units of [mu]g/L, whereas an inhalation unit risk is developed 
directly from a dose-response analysis using equivalent human 
concentrations already expressed in units of [mu]g/m3. Unit 
risk estimates often assume a standard intake rate (L/day drinking 
water or m3/day air) and body weight (kg), which may need to 
be reconciled with the exposure factors for the population of interest 
in an exposure assessment (see Section 4.4). Alternatively, when the 
slope factor for inhalation is in units of ppm, it may sometimes be 
termed the inhalation unit risk. Although unit risks have not been 
calculated in the past for dermal exposures, both exposures that are 
absorbed into the systemic circulation and those that remain in contact 
with the skin are also important.
    Risk-specific doses are derived from the slope factor or unit risk 
to estimate the dose associated with a specific risk level, for 
example, a one-in-a-million increased lifetime risk.
3.3.4. Nonlinear Extrapolation to Lower Doses
    A nonlinear extrapolation method can be used for cases with 
sufficient data to ascertain the mode of action and to conclude that it 
is not linear at low doses but with not enough data to support a 
toxicodynamic model that may be either nonlinear or linear at low 
doses. Nonlinear extrapolation having a significant biological support 
may be presented in addition to a linear approach when the available 
data and a weight of evidence evaluation support a nonlinear approach, 
but the data are not strong enough to ascertain the mode of action 
applying the Agency's mode of action framework. If the mode of action 
and other information can support chemical-specific modeling at low 
doses, it is preferable to default procedures.
    For cases where the tumors arise through a nonlinear mode of 
action, an oral reference dose or an inhalation reference 
concentration, or both, should be developed in accordance with EPA's 
established practice for developing such values, taking into 
consideration the factors summarized in the characterization of the POD 
(see Section 3.2.5). This approach expands the past focus of such 
reference values (previously reserved for effects other than cancer) to 
include carcinogenic effects determined to have a nonlinear mode of 
action. As with other health effects of concern, it is important to put 
cancer in perspective with the overall health impact of an exposure by 
comparing reference value calculations for cancer with those for other 
health effects.
    For effects other than cancer, reference values have been described 
as being based on the assumption of biological thresholds. The Agency's 
more current guidelines for these effects (U.S. EPA, 1996a, 1998b), 
however, do not use this assumption, citing the difficulty of 
empirically distinguishing a true threshold from a dose-response curve 
that is nonlinear at low doses.
    Economic and policy analysts need to know how the probability of 
cancer varies at exposures above the reference value and whether, and 
to what extent, there are health benefits from reducing exposures below 
the reference value. The risk assessment community is working to 
develop better methods to provide more useful information to economic 
and policy analysts.
3.3.5. Comparing and Combining Multiple Extrapolations
    When multiple estimates can be developed, all datasets should be 
considered and a judgment made about how best to represent the human 
cancer risk. Some options for presenting results include:
     Adding risk estimates derived from different tumor sites 
(NRC, 1994),
     Combining data from different datasets in a joint analysis 
(Putzrath and Ginevan, 1991; Stiteler et al., 1993; Vater et al., 
1993),
     Combining responses that operate through a common mode of 
action,
     Representing the overall response in each experiment by 
counting animals with any tumor showing a statistically significant 
increase,
     Presenting a range of results from multiple datasets (in 
this case, the dose-response assessment includes guidance on how to 
choose an appropriate value from the range),
     Choosing a single dataset if it can be justified as most 
representative of the overall response in humans, or
     A combination of these options.
    Cross-comparison of estimates from human and animal studies can 
provide a valuable risk perspective.
     Calculating an animal-derived slope factor and using it to 
estimate the risk expected in a human study can provide information 
with which to evaluate the human study design, for example, adequacy of 
exposure level and sample size.
     Calculating an upper-bound slope factor from a human study 
that does not show positive results but that has good exposure 
information, and comparing it to an animal-derived slope factor can 
indicate whether the animal and humans studies are consistent.

3.4. Extrapolation to Different Human Exposure Scenarios

    As described in the previous cancer guidelines, special problems 
arise when the human exposure situation of concern suggests exposure 
regimens, e.g., route and dosing schedule, that are substantially 
different from those used in the relevant animal studies. Unless there 
is evidence to the contrary in a particular case, the cumulative dose 
received over a lifetime, expressed as average daily exposure prorated 
over a lifetime, is recommended as an appropriate measure of exposure 
to a carcinogen. That is, the assumption is made that a high dose of a 
carcinogen received over a short period of time is equivalent to a 
corresponding low dose spread over a lifetime. This approach becomes 
more problematical as the exposures in question become more intense but 
less frequent, especially when there is evidence that the agent has 
shown dose-rate effects (U.S. EPA 1986a).

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    Accordingly, for lifetime human exposure scenarios that involve 
intermittent or varying levels of exposure, the prevailing practice has 
been to assess exposure by calculating a lifetime average daily 
exposure or dose (U.S. EPA, 1992a).
    For less-than-lifetime human exposure scenarios, too, the lifetime 
average daily exposure or dose has often been used. The use of these 
lifetime average exposure metrics was adopted with low-dose linear 
cancer assessments in mind. The lifetime averaging implies that less-
than-lifetime exposure is associated with a linearly proportional 
reduction of the lifetime risk, regardless of when exposures occur. 
Such averaging may be problematic in some situations. This can be 
illustrated using both the multistage model and the two-stage clonal 
expansion model that predict that short-duration risks are not 
necessarily proportional to exposure duration and can depend on the 
nature of the carcinogen and the timing of exposure (Goddard et al., 
1995; Murdoch et al., 1992). These examples indicate some circumstances 
in which use of a lifetime average daily dose (LADD) would 
underestimate cancer risk by two-to fivefold, and others in which it 
might overestimate risk (Murdoch et al., 1992). Thus, averaging over 
the duration of a lifestage or a critical window of exposure may be 
appropriate. As methodological research focuses on new approaches for 
estimating risks from less-than-lifetime exposures, methods and 
defaults can be expected to change.
    This highlights the importance for each dose-response assessment to 
critically evaluate all information pertaining to less-than-lifetime 
exposure. For example, detailed stop-exposure studies can provide 
information about the relationship between exposure duration, precursor 
effects, potential for reversibility, and tumor development. 
Toxicokinetic modeling can investigate differences in internal dose 
between short-term and long-term exposure or between intermittent and 
constant exposure. Persistence in the body can be useful in explaining 
long-term effects resulting from shorter-term exposures.
    For nonlinear cancer analyses, it may be appropriate to assess 
exposure by calculating a daily dose that is averaged over the exposure 
duration for the study (see Section 3.1.1). For example, when the 
analysis is based on precursor effects that result from less than a 
lifetime exposure, that exposure period may be used. This reflects an 
expectation that the precursor effects on which the analysis is based 
can result from less-than-lifetime exposure, bringing consistency to 
the methods used for dose-response assessment and exposure assessment 
in such cases. The dose-response assessment can provide a 
recommendation to exposure assessors about the averaging time that is 
appropriate to the mode of action and to the exposure duration of the 
scenario.

3.5. Extrapolation to Susceptible Populations and Lifestages

    The dose-response assessment strives to derive separate estimates 
for susceptible populations and lifestages so that these risks can be 
explicitly characterized. For a susceptible population, higher risks 
can be expected from exposures anytime during life, but this applies to 
only a portion of the general population (e.g., those bearing a 
particular genetic susceptibility). In contrast, for a susceptible 
lifestage, higher risks can be expected from exposures during only a 
portion of a lifetime, but everyone in the population may pass through 
those lifestages. Effects of exposures during a susceptible period are 
not equivalent to effects of exposures at other times; consequently, it 
is useful to estimate the risk attributable to exposures during each 
period.
    Depending on the data available, a tiered approach should be used 
to address susceptible populations and lifestages.
     When there is an epidemiologic study or an animal bioassay 
that reports quantitative results for susceptible individuals, the data 
should be analyzed to provide a separate risk estimate for those who 
are susceptible. If susceptibility pertains to a lifestage, it is 
useful to characterize the portion of the lifetime risk that can be 
attributed to the susceptible lifestage.
     When there are data on some risk-related parameters that 
allow comparison of the general population and susceptible individuals, 
the data should be analyzed with an eye toward adjusting the general 
population estimate for susceptible individuals. This analysis can 
range from toxicokinetic modeling that uses parameter values 
representative of susceptible individuals to more simply adjusting a 
general population estimate to reflect differences in important rate-
governing parameters. Care is taken to not make parameter adjustments 
in isolation, as the appropriate adjustment can depend on the 
interactions of several parameters; for example, the ratio of metabolic 
activation and clearance rates can be more appropriate than the 
activation rate alone (U.S. EPA, 1992b).
     In the absence of such agent-specific data, there is some 
general information to indicate that childhood can be a susceptible 
lifestage for exposure to some carcinogens (U.S. EPA, 2005); this 
warrants explicit consideration in each assessment. The potential for 
susceptibility from early-life exposure is expected to vary among 
specific agents and chemical classes. In addition, the concern that the 
dose-averaging generally used for assessing less-than-lifetime exposure 
is more likely to understate than overstate risk (see Section 3.4) 
contributes to the suggestion that alternative approaches be considered 
for assessing risks from less-than-lifetime exposure that occurs during 
childhood. Accompanying these cancer guidelines is the Supplemental 
Guidance that the Agency will use to assess risks from early-life 
exposure to potential carcinogens (U.S. EPA, 2005). The Supplemental 
Guidance may be updated to reflect new data and new understanding that 
may become available in the future.

3.6. Uncertainty

    The NRC (1983, 1994, 1996, 2002) has repeatedly advised that proper 
characterization of uncertainty is essential in risk assessment. An 
assessment that omits or underestimates uncertainty can leave 
decisionmakers with a false sense of confidence in estimates of risk. 
On the other hand, a high level of uncertainty does not imply that a 
risk assessment or a risk management action should be delayed (NRC, 
2002). Uncertainty in dose-response assessment can be classified as 
either model uncertainty or parameter uncertainty. A related concept, 
human variation, is discussed below. Assessments should discuss the 
significant uncertainties encountered in the analysis, distinguishing, 
if possible, between model uncertainty, parameter uncertainty, and 
human variation. Origins of these uncertainties can span a range, from 
a single causal thread supported by sparse data, to abundant 
information that presents multiple possible conclusions or that does 
not coalesce. As described in Section 2.6 and in Section 5.1, all 
contributing features should be noted.
    Model uncertainty refers to a lack of knowledge needed to determine 
which is the correct scientific theory on which to base a model. In 
risk assessment, model uncertainty is reflected in alternative choices 
for model structure, dose metrics, and extrapolation approaches. Other 
sources of model uncertainty concern whether surrogate data are 
appropriate, for example, using data on adults to make inferences about

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children. The full extent of model uncertainty usually cannot be 
quantified; a partial characterization can be obtained by comparing the 
results of alternative models. Model uncertainty is expressed through 
comparison of separate analyses from each model, coupled with a 
subjective probability statement, where feasible and appropriate, of 
the likelihood that each model might be correct (NRC, 1994).
    Some aspects of model uncertainty that should be addressed in an 
assessment include the use of animal models as a surrogate for humans, 
the influence of cross-species differences in metabolism and 
physiology, the use of effects observed at high doses as an indicator 
of the potential for effects at lower doses, the effect of using linear 
or nonlinear extrapolation to estimate risks, the use of using small 
samples and subgroups to make inferences about entire human populations 
or subpopulations with differential susceptibilities, and the use of 
experimental exposure regimens to make inferences about different human 
exposure scenarios (NRC, 2002).
    Toxicokinetic and toxicodynamic models are generally premised on 
site concordance across species, modeling, for example, the 
relationship between administered dose and liver tissue concentrations 
to predict increased incidences of liver cancer. This relationship, 
which can be observed in animals, is typically only inferred for 
humans. There are, however, numerous examples of an agent causing 
different cancers in different species. The assessment should discuss 
the relevant data that bear on this form of model uncertainty.
    Parameter uncertainty refers to a lack of knowledge about the 
values of a model's parameters. This leads to a distribution of values 
for each parameter. Common sources of parameter uncertainty include 
random measurement errors, systematic measurement errors, use of 
surrogate data instead of direct measurements, misclassification of 
exposure status, random sampling errors, and use of an unrepresentative 
sample. Most types of parameter uncertainty can be quantified by 
statistical analysis.
    Human variation refers to person-to-person differences in 
biological susceptibility or in exposure. Although both human variation 
and uncertainty can be characterized as ranges or distributions, they 
are fundamentally different concepts. Uncertainty can be reduced by 
further research that supports a model or improves a parameter 
estimate, but human variation is a reality that can be better 
characterized, but not reduced, by further research. Fields other than 
risk assessment use ``variation'' or ``variability'' to mean dispersion 
about a central value, including measurement errors and other random 
errors that risk assessors address as uncertainty.
    Probabilistic risk assessment, informed by expert judgment, has 
been used in exposure assessment to estimate human variation and 
uncertainty in lifetime average daily exposure concentration or dose. 
Probabilistic methods can be used in this exposure assessment 
application because the pertinent variables (for example, 
concentration, intake rate, exposure duration, and body weight) have 
been identified, their distributions can be observed, and the formula 
for combining the variables to estimate the lifetime average daily dose 
is well defined (see U.S. EPA, 1992a). Similarly, probabilistic methods 
can be applied in dose-response assessment when there is an 
understanding of the important parameters and their relationships, such 
as identification of the key determinants of human variation (for 
example, metabolic polymorphisms, hormone levels, and cell replication 
rates), observation of the distributions of these variables, and valid 
models for combining these variables. With appropriate data and expert 
judgment, formal approaches to probabilistic risk assessment can be 
applied to provide insight into the overall extent and dominant sources 
of human variation and uncertainty. In doing this, it is important to 
note that analyses that omit or underestimate some principal sources of 
variation or uncertainty could provide a misleadingly narrow 
description of the true extent of variation and uncertainty and give 
decisionmakers a false sense of confidence in estimates of risk. 
Specification of joint probability distributions is appropriate when 
variables are not independent of each other. In each case, the 
assessment should carefully consider the questions of uncertainty and 
human variation and discuss the extent to which there are data to 
address them.
    Probabilistic risk assessment has also been used in dose-response 
assessment to determine and distinguish the degree of uncertainty and 
variability in toxicokinetic and toxicodynamic modeling. Although this 
field is less advanced that probabilistic exposure assessment, progress 
is being made and these cancer guidelines are flexible enough to 
accommodate continuing advances in these approaches.
    Advances in uncertainty analysis are expected as the field 
develops. The cancer guidelines are intended to be flexible enough to 
incorporate additional approaches for characterizing uncertainty that 
have less commonly been used by regulatory agencies. In all scientific 
and engineering fields, data and research limitations often limit the 
application of established methods. A dearth of data is a particular 
problem when quantifying the probability distribution of model outputs. 
In many of these scientific and engineering disciplines, researchers 
have used rigorous expert elicitation methods to overcome the lack of 
peer-reviewed methods and data. Although expert elicitation has not 
been widely used in environmental risk assessment, several studies have 
applied this methodology as a tool for understanding quantitative risk. 
For example, expert elicitation has been used in chemical risk 
assessment and its associated uncertainty (e.g., Richmond, 1981; Renn, 
1999; Florig et al., 2001; Morgan et al., 2001; Willis et al., 2004), 
components of risk assessment such as hazard assessment and dose-
response evaluation (e.g., Hawkins and Graham 1988; Jelovsek et al., 
1990; Evans et al., 1994; IEc, 2004; U.S. EPA 2004) and exposure 
assessment (e.g., Whitfield and Wallsten, 1989; Hawkins and Evans, 
1989; Winkler et al., 1995; Stiber et al., 1999; Walker et al., 2001, 
2003; Van Der Fels-Klerx et al., 2002), and for evaluating other types 
of risks (e.g., North and Merkhofer, 1976; Fos and McLin, 1990). These 
cancer guidelines are flexible enough to accommodate the use of expert 
elicitation to characterize cancer risks, as a complement to the 
methods presented in the cancer guidelines. According to NRC (NRC, 
2002), the rigorous use of expert elicitation for the analyses of risks 
is considered to be quality science.

3.7. Dose-Response Characterization

    A dose-response characterization extracts the dose-response 
information needed in a full risk characterization (U.S. EPA, 2000b), 
including:
     Presentation of the recommended estimates (slope factors, 
reference doses, reference concentrations) and alternatives with 
significant biological support,
     A summary of the data supporting these estimates,
     A summary and explanation of the modeling approaches used,
     A description of any special features such as the 
development and consolidation of multiple estimates as detailed in 
Section 3.3.5,
     The POD narrative (see Section 3.2.5),

[[Page 17804]]

     A summary of the key defaults invoked,
     Identification of susceptible populations or lifestages 
and quantification of their differential susceptibility, and
     A discussion of the strengths and limitations of the dose-
response assessment, highlighting significant issues in developing risk 
estimates, alternative approaches considered equally plausible, and how 
these issues were resolved.
    All estimates should be accompanied by the weight of evidence 
descriptor and its narrative (see Section 2.5) to convey a sense of the 
qualitative uncertainty about whether the agent may or may not be 
carcinogenic.
    Slope factors generally represent an upper bound on the average 
risk in a population or the risk for a randomly selected individual but 
not the risk for a highly susceptible individual or group. Some 
individuals face a higher risk and some face a lower risk. The use of 
upper bounds generally is considered to be a health-protective approach 
for covering the risk to susceptible individuals, although the 
calculation of upper bounds is not based on susceptibility data. 
Similarly, exposure during some lifestages can contribute more or less 
to the total lifetime risk than do similar exposures at other times. 
The dose-response assessment characterizes, to the extent possible, the 
extent of these variations.
    Depending on the supporting data and modeling approach, a slope 
factor can have a mix of traits that tend to either estimate, 
overestimate, or underestimate risk.
    Some examples of traits that tend to overestimate risk include the 
following.
     The slope factor is derived from data on a highly 
susceptible animal strain.
     Linear extrapolation is used as a default and extends over 
several orders of magnitude.
     The largest of several slope factors is chosen.
    Some examples of traits that tend to underestimate risk include the 
following.
     Several tumor types were observed, but the slope factor is 
based on a subset of them.
     The study design does not include exposure during a 
susceptible lifestage, for example, perinatal exposure.
     The study population is of less-than-average 
susceptibility, for example, healthy adult workers.
     There is random exposure misclassification or random 
exposure measurement error in the study from which the slope factor is 
derived.
    Some examples of traits that inherently neither overestimate nor 
underestimate risk include the following.
     The slope factor is derived from data in humans or in an 
animal strain that responds like humans.
     Linear extrapolation is appropriate for the agent's mode 
of action.
     Environmental exposures are close to the observed data.
     Several slope factors for the same tumor are averaged or a 
slope factor is derived from pooled data from several studies.
     The slope factor is derived from the only suitable study.
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4. Exposure Assessment

    Exposure assessment is the determination (qualitative and 
quantitative) of the magnitude, frequency, and duration of exposure and 
internal dose (U.S. EPA, 1992a). This section provides a brief overview 
of exposure assessment principles, with an emphasis on issues related 
to carcinogenic risk assessment. The information presented here should 
be used in conjunction with other guidance documents, including 
Guidelines for Exposure Assessment (U.S. EPA, 1992a), Science Policy 
Council Handbook: Risk Characterization (U.S. EPA, 2000b), Exposure 
Factors Handbook (U.S. EPA, 1997c), the 1997 Policy for Use of 
Probabilistic Analysis in Risk Assessments (U.S. EPA, 1997d), and the 
1997 Guiding Principles for Monte Carlo Analysis (U.S. EPA, 1997e). In 
addition, program-specific guidelines for exposure assessment should be 
consulted.
    Exposure assessment generally consists of four major steps: 
defining the assessment questions, selecting or developing the 
conceptual and mathematical models, collecting data or selecting and 
evaluating available data, and exposure characterization. Each of these 
steps is briefly described below.

4.1. Defining the Assessment Questions

    In providing a clear and unambiguous statement of the purpose and 
scope of the exposure assessment (U.S. EPA, 1997e), consider the 
following.
     The management objectives of the assessment will determine 
whether deterministic screening level analyses are adequate or whether 
full probabilistic exposure characterization is needed.
     Identify and include all important sources (e.g., 
pesticide applications), pathways (e.g., food or water), and routes 
(e.g., ingestion, inhalation, and dermal) of exposure in the 
assessment. If a particular source, pathway, or route is omitted, a 
clear and transparent explanation should be provided.
     Separate analyses should be conducted for each definable 
subgroup within the population of interest. In particular, 
subpopulations or lifestages that are believed to be highly exposed or 
susceptible to a particular health effect should be studied. These 
include people with certain diseases or genetic susceptibilities and 
others whose behavior or physiology may lead to higher exposure or 
susceptibility. Consider the following examples:

--Physiological differences between men and women (e.g., body weight 
and inhalation rate) may lead to important differences in exposures. 
See, for example, the discussion in Exposure Factors Handbook (U.S. 
EPA, 1997c, Appendix 1A).
--Pregnant and lactating women may have exposures that differ from the 
general population (e.g., slightly higher water consumption) (U.S. EPA, 
1997c). Further, exposure to pregnant women may result in exposure to 
the developing fetus (NRC, 1993b).
--Children consume more food per body weight than do adults while 
consuming fewer types of foods, i.e., have a more limited diet (ILSI, 
1992; NRC, 1993b; U.S. EPA, 1997c). In addition, children engage in 
crawling and mouthing (i.e., putting hands and objects in the mouth) 
behaviors, which can increase their exposures.
--The elderly and disabled may have important differences in their 
exposures due to a more sedentary lifestyle (U.S. EPA, 1997c). In 
addition, the health status of this group may affect their 
susceptibility to the detrimental effects of exposure.

    For further guidance, see Guidelines for Exposure Assessment (U.S. 
EPA, 1992a, Sec.  3).

4.2. Selecting or Developing the Conceptual and Mathematical Models

    Carcinogen risk assessment models have generally been based on the 
premise that risk is proportional to cumulative lifetime dose. For 
lifetime human exposure scenarios, therefore, the exposure metric used 
for carcinogenic risk assessment has been the lifetime average daily 
dose (LADD) or, in the case of inhalation exposure, the lifetime 
average exposure concentration. These metrics are typically used in 
conjunction with the corresponding slope factor to calculate individual 
excess cancer risk. The LADD is typically an estimate of the daily 
intake of a carcinogenic agent throughout the entire life of an 
individual, while the lifetime average exposure concentration is the 
corresponding estimate of average exposure concentration for the 
carcinogenic agent over the entire life of an individual. Depending on 
the objectives of the assessment, the LADD or lifetime average exposure 
concentration may be calculated deterministically (using point 
estimates for each factor to derive a point estimate of the exposure) 
or stochastically (using probability distributions to represent each 
factor and such techniques as Monte Carlo analysis to derive a 
distribution of the LADD) (U.S. EPA, 1997e). Stochastic analyses may 
help to identify certain population segments or lifestages that are 
highly exposed and may need to be assessed as a special subgroup. For 
further guidance, see Guidelines for Exposure Assessment (U.S. EPA, 
1992a, Sec.  5.3.5.2 ). As methodological research focuses on new 
approaches for estimating risks from less-than-lifetime exposures, 
methods and defaults can be expected to change.
    There may be cases where the mode of action indicates that dose 
rates are important in the carcinogenic process. In these cases, short-
term, less-than-lifetime exposure estimates may be more appropriate 
than the LADD for risk assessment. This may be the case when a 
nonlinear dose-response approach is used (see Section 3.3.4).

4.3. Collecting Data or Selecting and Evaluating Available Data

    After the assessment questions have been defined and the conceptual 
and mathematical models have been developed, it is important to compile 
and evaluate existing data or, if necessary, to collect new data. 
Depending on the exposure scenario under consideration, data on a wide 
variety of exposure factors may be needed. EPA's Exposure Factors 
Handbook (U.S. EPA, 1997c) contains a large compilation of exposure 
data, with some analysis and recommendations. Some of these data are 
organized by age groups to assist with assessing such subgroups as 
children. See, for example, Exposure Factors Handbook (U.S. EPA, 1997c, 
Volume 1, Chapter 3). When using these existing data, it is important 
to evaluate the quality of the data and the extent to which the data 
are representative of the population under consideration. EPA's (U.S. 
EPA, 2000d) and OMB's (OMB 2002) guidance on information quality, as 
well as program-specific guidances can provide further assistance for 
evaluating existing data.
    When existing data fail to provide an adequate surrogate for the 
needs of a particular assessment, it is important to collect new data. 
Such data collection efforts should be guided by the references listed 
above (e.g., Guidance for Data Quality Assessment and program-specific 
guidance). Once again, subpopulations or lifestages of concern are an 
important consideration in any data collection effort.
4.3.1. Adjusting Unit Risks for Highly Exposed Populations and 
Lifestages
    Unit risk estimates that have been developed in the dose-response 
assessment often assumed standard adult intake rates. When an exposure 
assessment focuses on a population or lifestage with differential 
exposure, good exposure assessment practice would replace the standard 
intake rates

[[Page 17807]]

with values representative of the exposed population. Small changes in 
exposure assessments can be approximated by using linearly proportional 
adjustments of exposure parameters, but a more accurate integrative 
analysis may require an analysis stratified by exposure duration (see 
Section 5.1).

    For example, to adjust the drinking water unit risk for an 
active population that drinks 4 L/day (instead of 2 L/day), multiply 
the unit risk by 2.

    Because children drink more water relative to their body weight 
than do adults (U.S. EPA, 2002d), adjustments to unit risk estimates 
are warranted whenever they are applied in an assessment of childhood 
exposure.

    For example, to adjust the drinking water unit risk for a 9-kg 
infant who drinks 1 L/day (instead of a 70-kg adult who drinks 2 L/
day), multiply the unit risk by [(1 L/day) / (9 kg)] / [(2 L/day) / 
(70 kg)] = 3.9.

    Inhalation dosimetry is employed to derive the human equivalent 
exposure concentrations on which inhalation unit risks, and reference 
concentrations, are based (U.S. EPA, 1994). As described previously 
(see Sections 3.1.2, 3.1.3), different dosimetry methods may be 
employed depending on the availability of relevant data and chemical-
specific characteristics of the pollutant. Consideration of lifestage-
particular physiological characteristics in the dosimetry analysis may 
result in a refinement to the human equivalent concentration (HEC) to 
insure relevance in risk assessment across lifestages, or might 
conceivably conclude with multiple HECs, and corresponding inhalation 
unit risk values (e.g., separate for childhood and adulthood).
    The dose-response assessment discusses the key sources of 
uncertainty in estimating dosimetry, including any related to 
lifestage. Review of this discussion and of the dosimetric analysis 
performed in deriving the HEC and resultant unit risk will assist in 
the appropriate application of inhalation unit risk values to exposure 
across lifestages.

4.4. Exposure Characterization

    The exposure characterization is a technical characterization that 
presents the assessment results and supports the risk characterization. 
It provides a statement of the purpose, scope, and approach used in the 
assessment, identifying the exposure scenarios and population subgroups 
covered. It provides estimates of the magnitude, frequency, duration, 
and distribution of exposures among members of the exposed population 
as the data permit. It identifies and compares the contribution of 
different sources, pathways, and routes of exposure. In particular, a 
qualitative discussion of the strengths and limitations (uncertainties) 
of the data and models are presented.
    The discussion of uncertainties is a critical component of the 
exposure characterization. Uncertainties can arise out of problems with 
the conceptual and mathematical models. Uncertainties can also arise 
from poor data quality and data that are not quite representative of 
the population or scenario of interest. Consider the following examples 
of uncertainties.
     National data (i.e., data collected to represent the 
entire U.S. population) may not be representative of exposures 
occurring within a regional or local population.
     Use of short-term data to infer chronic, lifetime 
exposures should be done with caution. Use of short-term data to 
estimate long-term exposures has the tendency to underestimate the 
number of people exposed while overestimating the exposure levels 
experienced by those in the upper end (i.e., above the 90th percentile) 
of the exposure distribution. For further guidance, refer to Guidelines 
for Exposure Assessment (U.S. EPA, 1992a, Sec.  5.3.1).
     Children's behavior, including their more limited diet, 
may lead to relatively high but intermittent exposures. This pattern of 
exposure, ``one that gradually declines over the developmental period 
and which remains relatively constant thereafter'' is not accounted for 
in the LADD model (ILSI, 1992). Further, the physiological 
characteristics of children may lead to important differences in 
exposure. Some of these differences can be accounted for in the LADD 
model. For further guidance, see Guidelines for Exposure Assessment 
(U.S. EPA, 1992a, Sec.  5.3.5.2).
    Overall, the exposure characterization should provide a full 
description of the sources, pathways, and routes of exposure. The 
characterization also should include a full description of the 
populations assessed. In particular, highly exposed or susceptible 
subpopulation or lifestage should be discussed. For further guidance on 
the exposure characterization, consult Guidelines for Exposure 
Assessment (U.S. EPA, 1992a), the Policy and Guidance for Risk 
Characterization (U.S. EPA, 2000b,1995) and EPA's Rule Writer's Guide 
to Executive Order 13045 (especially Attachment C: Technical Support 
for Risk Assessors--Suggestions for Characterizing Risks to Children 
[U.S. EPA, 1998d]).

5. Risk Characterization

5.1. Purpose

    EPA has developed general guidance on risk characterization for use 
in its risk assessment activities. The core of EPA's risk 
characterization policy (U.S. EPA, 2000b, 1995) includes the following.

    Each risk assessment prepared in support of decision making at 
EPA should include a risk characterization that follows the 
principles and reflects the values outlined in this policy. A risk 
characterization should be prepared in a manner that is clear, 
transparent, reasonable, and consistent with other risk 
characterizations of similar scope prepared across programs in the 
Agency. Further, discussion of risk in all EPA reports, 
presentations, decision packages, and other documents should be 
substantively consistent with the risk characterization. The nature 
of the risk characterization will depend upon the information 
available, the regulatory application of the risk information, and 
the resources (including time) available. In all cases, however, the 
assessment should identify and discuss all the major issues 
associated with determining the nature and extent of the risk and 
provide commentary on any constraints limiting fuller exposition.

    Risk characterization should be carried out in accordance with the 
EPA (U.S. EPA, 2002a) and OMB (2002) information quality guidelines. 
EPA's risk characterization handbook (U.S. EPA, 2000b) provides 
detailed guidance to Agency staff. The discussion below does not 
attempt to duplicate this material, but it summarizes its applicability 
to carcinogen risk assessment.
    The risk characterization includes a summary for the risk manager 
in a nontechnical discussion that minimizes the use of technical terms. 
It is an appraisal of the science that informs the risk manager in 
public health decisions, as do other decision-making analyses of 
economic, social, or technology issues. It also serves the needs of 
other interested readers. The summary is an information resource for 
preparing risk communication information, but being somewhat more 
technical than desired for communication with the general public, is 
not itself the usual vehicle for communication with every audience.
    The risk characterization also brings together the assessments of 
hazard, dose response, and exposure to make risk estimates for the 
exposure scenarios of interest. This analysis that follows the summary 
is generally much more extensive. It typically will identify exposure 
scenarios of interest in decision making and present risk analyses 
associated with them. Some of the analyses may concern scenarios in

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several media; others may examine, for example, only drinking water 
risks. As these cancer guidelines allow different hazard 
characterizations and different potencies for specified conditions, 
e.g., exposure level, route of exposure, or lifestage, some of the 
integrative analyses may need to be stratified to accommodate the 
appropriate combinations of parameters across relevant exposure 
durations.
    In constructing high end estimates of risk, the assessor should 
bear in mind that the high-end risk is a plausible estimate of the risk 
for those persons at the upper end of the risk distribution (U.S. EPA, 
1992a). The intent of this approach is to convey an estimate of risk in 
the upper range of the distribution, but to avoid estimates that are 
beyond the true distribution. Overly conservative assumptions, when 
combined, can lead to unrealistic estimates of risk. This means that 
when constructing estimates from a series of factors (e.g., emissions, 
exposure, and unit risk estimates) not all factors should be set to 
values that maximize exposure, dose, or effect, since this will almost 
always lead to an estimate that is above the 99th-percentile confidence 
level and may be of limited use to decisionmakers. This is particularly 
problematic when using unbounded lognormal factor distributions.
    While it is an appropriate aim to assure protection of health and 
the environment in the face of scientific uncertainty, common sense, 
reasonable applications of assumptions and policy, and transparency are 
essential to avoid unrealistically high estimates. It is also important 
to inform risk managers of the final distribution of risk estimates 
(U.S. EPA, 2000b; 1995). Otherwise, risk management decisions may be 
made on varying levels of conservatism, leading to misplaced risk 
priorities and potentially higher overall risks. (Nichols and 
Zeckhauser,1986; Zeckhauser and Viscusi,1990).
    The risk characterization presents an integrated and balanced 
picture of the analysis of the hazard, dose-response, and exposure. The 
risk analyst should provide summaries of the evidence and results and 
describe the quality of available data and the degree of confidence to 
be placed in the risk estimates. Important features include the 
constraints of available data and the state of knowledge, significant 
scientific issues, and significant science and science policy choices 
that were made when alternative interpretations of data exist (U.S. 
EPA, 1995, 2000b). Choices made about using data or default options in 
the assessment are explicitly discussed in the course of analysis, and 
if a choice is a significant issue, it is highlighted in the summary. 
In situations where there are alternative approaches for a risk 
assessment that have significant biological support, the decisionmaker 
can be informed by the presentation of these alternatives along with 
their strengths and uncertainties.

5.2. Application

    Risk characterization is a necessary part of generating any Agency 
report on risk, whether the report is preliminary--to support 
allocation of resources toward further study--or comprehensive--to 
support regulatory decisions. In the former case, the detail and 
sophistication of the characterization are appropriately small in 
scale; in the latter case, appropriately extensive. Even if a document 
covers only parts of a risk assessment (hazard and dose-response 
analyses, for instance), the results of these are characterized.
    Risk assessment is an iterative process that grows in depth and 
scope in stages from screening for priority making to preliminary 
estimation to fuller examination in support of complex regulatory 
decision making. Default options may be used at any stage, but they are 
predominant at screening stages and are used less as more data are 
gathered and incorporated at later stages. Various provisions in EPA-
administered statutes require decisions based on differing findings for 
which differing degrees of analysis are appropriate. There are close to 
30 provisions within the major statutes that require decisions based on 
risk, hazard, or exposure assessment. For example, Agency review of 
pre-manufacture notices under Section 5 of the Toxic Substances Control 
Act relies on screening analyses, whereas requirements for industry 
testing under Section 4 of that Act rely on preliminary analyses of 
risk or simply of exposure. In comparison, air quality criteria under 
the Clean Air Act rest on a rich data collection and are required by 
statute to undergo periodic reassessment. There are provisions that 
require ranking of hazards of numerous pollutants--which may be 
addressed through a screening level of analysis--and other provisions 
for which a full assessment of risk is more appropriate.
    Given this range in the scope and depth of analyses, not all risk 
characterizations can or should be equal in coverage or depth. The risk 
assessor should carefully decide which issues in a particular 
assessment are important to present, choosing those that are noteworthy 
in their impact on results. For example, health effect assessments 
typically rely on animal data because human data are rarely available. 
The objective of characterization of the use of animal data is not to 
recount generic issues about interpreting and using animal data; Agency 
guidance documents cover these issues. Rather, the objective is to 
highlight any significant issues that arose within the particular 
assessment being characterized and inform the reader about significant 
uncertainties that affect conclusions.

5.3. Presentation of the Risk Characterization Summary

    The presentation is a nontechnical discussion of important 
conclusions, issues, and uncertainties that uses the hazard, dose 
response, exposure, and integrative analyses for technical support. The 
primary technical supports within the risk assessment are the hazard 
characterization, dose-response characterization, and exposure 
characterization described in these cancer guidelines. The risk 
characterization is derived from these. The presentation should fulfill 
the aims outlined in the purpose section above.

5.4. Content of the Risk Characterization Summary

    Specific guidance on hazard, dose-response, and exposure 
characterization appears in previous sections. Overall, the risk 
characterization routinely includes the following, capturing the 
important items covered in hazard, dose response, and exposure 
characterization:
     Primary conclusions about hazard, dose response, and 
exposure, including alternatives with significant biological support;
     Nature of key supporting information and analytic methods;
     Risk estimates and their attendant uncertainties, 
including key uses of default options when data are missing or 
uncertain.

--With linear extrapolations, risk below the POD is typically 
approximated by multiplying the slope factor by an estimate of 
exposure, i.e., Risk = Slope Factor x Exposure. For exposure levels 
above the POD, the dose-response model is used instead of this 
approximation.
--With nonlinear extrapolations, the method of risk assessment depends 
on the procedure used. If a nonlinear dose-response function has been 
determined, it can be used with the expected exposure to estimate a 
risk. If an RfD or RfC was calculated, the hazard can be expressed as a 
hazard quotient (HQ), defined as the ratio of an exposure estimate over 
the

[[Page 17809]]

reference dose (RfD) or reference concentration (RfC), i.e., HQ = 
Exposure / (RfD or RfC). From the hazard quotient, it can generally be 
inferred whether the nonlinear mode of action is relevant at the 
environmental exposure level in question;

     Statement of the extent of extrapolation of risk estimates 
from observed data to exposure levels of interest and its implications 
for certainty or uncertainty in quantifying risk. The extent of 
extrapolation can be expressed as a margin of exposure (MOE), defined 
as the ratio of the POD over an exposure estimate (MOE = POD / 
Exposure);
     Significant strengths and limitations of the data and 
analyses, including any major peer review issues;
     Appropriate comparison with similar EPA risk analyses or 
common risks with which people may be familiar; and
     Comparison with all appropriate assessments of the same 
problem by others.
    It is often difficult to know a priori when or how different 
results of a cancer risk assessment are likely to be used by Agency 
economists, policy analysts, and decisionmakers, so it is important 
that the resulting characterizations include the necessary information 
for these analyses to the extent practicable. OMB and EPA guidelines 
for benefit-cost analysis require expected or central estimates of risk 
and information on the uncertainty of the estimate when it is possible 
or practicable. The extent of the uncertainty information needed for 
analysis depends, in part, on the scale of the policy being considered, 
with formal quantitative analysis of uncertainty being required in some 
cases.\6\ OMB Circular A-4 (OMB, 2003) emphasizes that agencies 
``should try to provide some estimate of the probability distribution 
of regulatory benefits and costs.'' These OMB guidelines note, 
``Whenever it is possible to characterize quantitatively the 
probability distribution, some estimates of expected value * * * must 
be provided in addition to ranges, variances, specified low-end and 
high-end percentile estimates, and other characteristics of the 
distribution.'' The risk characterization should therefore include, 
where practicable, expected or central estimates of risk, as well as 
upper and lower bounds, e.g., confidence limits, based on the POD, if 
not a full characterization of uncertainty of the risk. As discussed in 
EPA's Guidelines for Ensuring and Maximizing the Quality, Objectivity, 
Utility, and Integrity of Information Disseminated by the Environmental 
Protection Agency (Appendix B), statutory mandates, such as the Safe 
Drinking Water Act, the Food Quality Protection Act, and the Clean Air 
Act, call for the Agency to generate specific kinds of risk 
information, and thus these updated cancer assessment guidelines should 
be read in conjunction with the Agency's statutory mandates regarding 
risk assessment.
---------------------------------------------------------------------------

    \6\ Specifically, OMB guidelines state: ``For rules that exceed 
the $1 billion annual [economic effects] threshold, a formal 
quantitative analysis of uncertainty is required. For rules with 
annual benefits and/or costs in the range from 100 million to $1 
billion, you should seek to use more rigorous approaches with higher 
consequence rules.'' (OMB, 2003, page 158)
---------------------------------------------------------------------------

Appendix A: Major Default Options

    This discussion covers the major default options commonly employed 
when data are missing or sufficiently uncertain in a cancer risk 
assessment, as adopted in these cancer guidelines. These options are 
predominantly inferences that help use the data observed under 
empirical conditions in order to estimate events and outcomes under 
environmental conditions. Several inferential issues arise when effects 
seen in a subpopulation of humans or animals are used to infer 
potential effects in the population of environmentally exposed humans. 
Several more inferential issues arise in extrapolating the exposure-
effect relationship observed empirically to lower-exposure 
environmental conditions. The following issues cover the major default 
areas.
     Is the presence or absence of effects observed in a human 
population predictive of effects in another exposed human population?
     Is the presence or absence of effects observed in an 
animal population predictive of effects in exposed humans?
     How do metabolic pathways relate across species and among 
different age groups and between sexes in humans?
     How do toxicokinetic processes relate across species and 
among different age groups and between sexes in humans?
     What is the relationship between the observed dose-
response relationship to the relationship at lower doses?

Is the Presence or Absence of Effects Observed in a Human Population 
Predictive of Effects in Another Exposed Human Population?

    When cancer effects in exposed humans are attributed to exposure to 
an agent, the default option is that the resulting data are predictive 
of cancer in any other exposed human population. Most studies 
investigating cancer outcomes in humans from exposure to agents are 
often studies of occupationally exposed humans. By sex, age, and 
general health, workers may not be representative of the general 
population exposed environmentally to the same agents. In such studies 
there is no opportunity to observe subpopulations who are likely to be 
under represented, such as fetuses, infants and children, women, or 
people in poor health, who may respond differently from healthy 
workers. Therefore, it is understood that this option could still 
underestimate the response of certain human subpopulations (NRC, 1993b, 
1994).
    When cancer effects are not found in an exposed human population, 
this information by itself is not generally sufficient to conclude that 
the agent poses no carcinogenic hazard to this or other populations of 
potentially exposed humans, including susceptible subpopulations or 
lifestages. This is because epidemiologic studies often have low power 
to detect and attribute responses and typically evaluate cancer 
potential in a restricted population (e.g., by age, healthy workers). 
The topic of susceptibility and variation is addressed further in the 
discussion below of quantitative default options about dose-response 
relationships. Well-conducted studies that fail to detect a 
statistically significant positive association, however, may have value 
and should be judged on their merits, including population size, 
duration of the study, the quality of the exposure characterization and 
measures of outcome, and the magnitude and duration of the exposure.
    There is not yet enough knowledge to form a basis for any generally 
applicable qualitative or quantitative inference to compensate for the 
gap in knowledge concerning other populations. In these cancer 
guidelines, this problem is left to analysis in individual cases, to be 
attended to with further general guidance as future research and 
information allow. When information on a susceptible subpopulation or 
lifestage exists, it will be used. For example, an agent such as 
diethylstilbestrol (DES) causes a rare form of vaginal cancer (clear-
cell adenocarcinoma) (Herbst et al., 1971) in about 1 per 1000 of adult 
women whose mothers were exposed during pregnancy (Hatch et al., 1998).

[[Page 17810]]

Is the Presence or Absence of Effects Observed in an Animal Population 
Predictive of Effects in Exposed Humans?

    The default option is that positive effects in animal cancer 
studies indicate that the agent under study can have carcinogenic 
potential in humans. Thus, if no adequate human or mode of action data 
are present, positive effects in animal cancer studies are a basis for 
assessing the carcinogenic hazard to humans. This option is a public 
health-protective policy, and it is both appropriate and necessary, 
given that we do not test for carcinogenicity in humans. The option is 
supported by the fact that nearly all of the agents known to cause 
cancer in humans are carcinogenic in animals in tests that have 
adequate protocols (IARC, 1994; Tomatis et al., 1989; Huff, 1994). 
Moreover, almost one-third of human carcinogens were identified 
subsequent to animal testing (Huff, 1993). Further support is provided 
by research on the molecular biology of cancer processes, which has 
shown that the mechanisms of control of cell growth and differentiation 
are remarkably homologous among species and highly conserved in 
evolution. Nevertheless, the same research tools that have enabled 
recognition of the nature and commonality of cancer processes at the 
molecular level also have the power to reveal differences and instances 
in which animal responses are not relevant to humans (Lijinsky, 1993; 
U.S. EPA, 1991b). Under these cancer guidelines, available mode of 
action information is studied for its implications in both hazard and 
dose-response assessment and its ability to obviate default options.
    There may be instances in which the use of an animal model would 
identify a hazard in animals that is not truly a hazard in humans 
(e.g., the alpha-2u-globulin association with renal neoplasia in male 
rats [U.S. EPA, 1991b]). The extent to which animal studies may yield 
false positive indications for humans is a matter of scientific debate. 
To demonstrate that a response in animals is not relevant to any human 
situation, adequate data to assess the relevancy issue are important.
    In general, while effects seen at the highest dose tested are 
assumed to be appropriate for assessment, it is necessary that the 
experimental conditions be scrutinized. Animal studies are conducted at 
high doses in order to provide statistical power, the highest dose 
being one that is minimally toxic (maximum tolerated dose or MTD). 
Consequently, the question often arises of whether a carcinogenic 
effect at the highest dose may be a consequence of cell killing with 
compensatory cell replication or of general physiological disruption 
rather than inherent carcinogenicity of the tested agent. There is 
little doubt that this may happen in some cases, but skepticism exists 
among some scientists that it is a pervasive problem (Ames and Gold, 
1990; Melnick et al., 1993; Barrett, 1993). If adequate data 
demonstrate that the effects are solely the result of excessive 
toxicity rather than carcinogenicity of the tested agent per se, then 
the effects may be regarded as not appropriate to include in assessment 
of the potential for human carcinogenicity of the agent. This is a 
matter of expert judgment, with consideration given to all of the data 
available about the agent, including effects in other toxicity studies, 
structure-activity relationships, and effects on growth control and 
differentiation.
    When cancer effects are not found in well-conducted animal cancer 
studies in two or more appropriate species and other information does 
not support the carcinogenic potential of the agent, these data provide 
a basis for concluding that the agent is not likely to possess human 
carcinogenic potential, in the absence of human data to the contrary. 
This default option about lack of cancer effects has limitations. It is 
recognized that animal studies (and epidemiologic studies as well) have 
very low power to detect cancer effects. Detection of a 10% tumor 
incidence is generally the limit of power with standard protocols for 
animal studies (with the exception of rare tumors that are virtually 
markers for a particular agent, e.g., angiosarcoma caused by vinyl 
chloride). In some situations, the tested animal species may not be 
predictive of effects in humans; for example, arsenic shows only 
minimal or no effect in animals, whereas it is clearly positive in 
humans. Therefore, it is important to consider other information as 
well; absence of mutagenic activity or absence of carcinogenic activity 
among structural analogues can increase the confidence that negative 
results in animal studies indicate a lack of human hazard.
    Another limitation is that standard animal study protocols are not 
yet available for effectively studying perinatal effects. The potential 
for effects on the very young generally should be considered 
separately. Under existing Agency policy (U.S. EPA, 1997a, b), 
perinatal studies accomplished by modification of existing adult 
bioassay protocols are important in special circumstances.
    Target organ concordance is not a prerequisite for evaluating the 
implications of animal study results for humans. Target organs of 
carcinogenesis for agents that cause cancer in both animals and humans 
are most often concordant at one or more sites (Tomatis et al., 1989; 
Huff, 1994). However, concordance by site is not uniform. The 
mechanisms of control of cell growth and differentiation are concordant 
among species, but there are marked differences among species in the 
way control is managed in various tissues. For example, in humans, 
mutations of the tumor suppressor genes p53 and retinoblastoma are 
frequently observed genetic changes in tumors. These tumor-suppressor 
genes are also observed to be operating in some rodent tissues, but 
other growth control mechanisms predominate in other rodent tissues. 
Thus, an animal response may be due to changes in a control that are 
relevant to humans but appear in animals in a different way.
    However, it is appropriate under these cancer guidelines to 
consider the influences of route of exposure, metabolism, and, 
particularly, some modes of action that may either support or not 
support target organ concordance between animals and humans. When data 
allow, these influences are considered in deciding whether agent-, 
species-, or organ-specific situations are appropriate to use in 
preference to this default assumption (NRC, 1994). In contrast, use of 
toxicokinetic modeling inherently assumes site concordance, as these 
models are used to estimate delivered dose to a particular tissue or 
organ in humans on the basis of the same tissue or organ from animal 
data.
    The default is to include benign tumors observed in animal studies 
in the assessment of animal tumor incidence, if such tumors have the 
capacity to progress to the malignancies with which they are 
associated. This default is consistent with the approach of the 
National Toxicology Program and the International Agency for Research 
on Cancer and is more protective of public health than not including 
benign tumors in the assessment; benign and malignant tumors are 
treated as representative of related responses to the test agent 
(McConnell et al., 1986), which is scientifically appropriate. 
Nonetheless, in assessing findings from animal studies, a greater 
proportion of malignancy is weighed more heavily than is a response 
with a greater proportion of benign tumors. Greater frequency of 
malignancy of a particular tumor type in comparison with other tumor 
responses observed in an animal study is also a factor to be considered

[[Page 17811]]

in selecting the response to be used in dose-response assessment.
    Benign tumors that are not observed to progress to malignancy are 
assessed on a case-by-case basis. There is a range of possibilities for 
the overall significance of benign tumors. They may deserve attention 
because they are serious health problems even though they are not 
malignant; for instance, benign tumors may be a health risk because of 
their effect on the function of a target tissue, such as the brain. 
They may be significant indicators of the need for further testing of 
an agent if they are observed in a short-term test protocol, or such an 
observation may add to the overall weight of evidence if the same agent 
causes malignancies in a long-term study. Knowledge of the mode of 
action associated with a benign tumor response may aid in the 
interpretation of other tumor responses associated with the same agent.

How Do Metabolic Pathways Relate Across Species and Among Different Age 
Groups and Between Sexes in Humans?

    The default option is that there is a similarity of the basic 
pathways of metabolism and the occurrence of metabolites in tissues in 
regard to the species-to-species extrapolation of cancer hazard and 
risk. If comparative metabolism studies were to show no similarity 
between the tested species and humans and a metabolite(s) was the 
active form, there would be less support for an inference that the 
animal response(s) relates to humans. In other cases, parameters of 
metabolism may vary quantitatively between species; this becomes a 
factor in deciding on an appropriate human-equivalent dose based on 
animal studies, optimally in the context of a toxicokinetic model. 
Although the basic pathways are assumed to be the same among humans, 
the presence of polymorphisms in the general population and factors 
such as the maturation of the pathways in infants should be considered. 
The active form of an agent may be present to differing degrees, or it 
may be completely absent, which may result in greater or lesser risk 
for subpopulations.

How Do Toxicokinetic Processes Relate Across Species and Among 
Different Age Groups and Between Sexes in Humans?

    A major issue is how to estimate human-equivalent doses in 
extrapolating from animal studies. As a default for oral exposure, a 
human equivalent dose for adults is estimated from data on another 
species by an adjustment of animal applied oral dose by a scaling 
factor based on body weight to the \3/4\ power. The same factor is used 
for children because it is slightly more protective than using 
children's body weight (see Section 3.1.3). This adjustment factor is 
used because it represents scaling of metabolic rate across animals of 
different size. Because the factor adjusts for a parameter that can be 
improved on and brought into more sophisticated toxicokinetic modeling 
when such data become available, they are usually preferable to the 
default option.
    For inhalation exposure, a human equivalent dose for adults is 
estimated by default methodologies that provide estimates of lung 
deposition and internal dose (U.S. EPA, 1994). The methodologies can be 
refined to more sophisticated forms with data on toxicokinetic and 
metabolic parameters of the specific agent. This default option, like 
the one for oral exposure, is selected in part because it lays a 
foundation for incorporating better data. The use of information to 
improve dose estimation from applied to internal to delivered dose is 
encouraged, including use of toxicokinetic modeling instead of any 
default, where data are available.
    There are important differences between infants, adults, and older 
adults in the processes of absorption, distribution, and elimination; 
for example, infants tend to absorb metals through the gut more rapidly 
and more efficiently than do older children or adults (Calabrese, 
1986). Renal elimination is also not as efficient in infants. Although 
these processes reach adult competency at about the time of weaning, 
they may have important implications, particularly when the dose-
response relationship for an agent is considered to be nonlinear and 
there is an exposure scenario disproportionately affecting infants, 
because in these cases the magnitude of dose is more pertinent than the 
usual approach in linear extrapolation of averaging dose across a 
lifetime. Efficiency of intestinal absorption in older adults tends to 
be generally less overall for most chemicals. Another notable 
difference is that, post-weaning (about 1 year), children have a higher 
metabolic rate than do adults (Renwick, 1998), and they may toxify or 
detoxify agents at a correspondingly higher rate.
    For a route-to-route exposure extrapolation, the default option is 
that an agent that causes internal tumors by one route of exposure will 
be carcinogenic by another route if it is absorbed by the second route 
to give an internal dose. This is a qualitative option and is 
considered to be public-health protective. The rationale is that for 
internal tumors an internal dose is significant no matter what the 
route of exposure. Additionally, the metabolism of the agent will be 
qualitatively the same for an internal dose. The issue of quantitative 
extrapolation of the dose-response relationship from one route to 
another is addressed case by case. Quantitative extrapolation is 
complicated by considerations such as first-pass metabolism.

What Is the Correlation of the Observed Dose-Response Relationship to 
the Relationship at Lower Doses?

    If sufficient data are available, a biologically based model for 
both the observed range and extrapolation below that range may be used. 
Although no standard biologically based models are in existence, an 
agent-specific model may be developed if extensive data exist in a 
particular case and the purpose of the assessment justifies the 
investment of the resources needed. The default procedure for the 
observed range of data when a biologically based model is not used is 
to use a curve-fitting model for incidence data.
    In the absence of data supporting a biologically based model for 
extrapolation outside of the observed range, the choice of approach is 
based on the view of mode of action of the agent arrived at in the 
hazard assessment. If more than one approach (e.g., both a nonlinear 
and linear approach) are supported by the data, they should be used and 
presented to the decisionmaker.
    A linear extrapolation approach is used when the mode of action 
information is supportive of linearity or mode of action is not 
understood. The linear approach is used when a view of the mode of 
action indicates a linear response, for example, when a conclusion is 
made that an agent directly causes alterations in DNA, a kind of 
interaction that not only theoretically requires one reaction but also 
is likely to be additive to ongoing, spontaneous gene mutation. Other 
kinds of activity may have linear implications, for example, linear 
rate-limiting steps would also support a linear procedure. The linear 
approach is to draw a straight line between a point of departure from 
observed data, generally as a default, an LED chosen to be 
representative of the lower end of the observed range, and the origin 
(zero incremental dose, zero incremental response). This approach is 
generally considered to be public-health protective.
    The linear default is thought to generally provide an upper-bound 
calculation of potential risk at low doses, for example, a

[[Page 17812]]

1/100,000 to 1/1,000,000 risk. This upper bound is thought to be 
public-health protective at low doses for the range of human variation, 
considering the typical Agency target range for risk management of 1/
1,000,000 to 1/10,000, although it may not completely be so (Bois et 
al., 1995) if pre-existing disease or genetic constitution place a 
percentage of the population at greater risk from exposure to 
carcinogens. The question of what may be the actual variation in human 
susceptibility is one that was discussed in general in the NRC (1994) 
report, as well as the NRC report on pesticides in children and infants 
(NRC, 1993b). NRC has recommended research on the question, and EPA and 
other agencies are conducting such research. Given the current state of 
knowledge, EPA will assume that the linear default procedure adequately 
accounts for human variation unless there is case-specific information 
for a given agent or mode of action that indicates a particularly 
susceptible subpopulation or lifestage, in which case the special 
information will be used.
    When adequate data on mode of action provide sufficient evidence to 
support a nonlinear mode of action for the general population and/or 
any subpopulations of concern, a different approach--a reference dose/
reference concentration that assumes that nonlinearity--is used. The 
POD is again generally an BMDL when incidence data are modeled. A 
sufficient basis to support this nonlinear procedure is likely to 
include data on responses that are key events integral to the 
carcinogenic process. This means that the POD may be based on these 
precursor response data, for example, hormone levels or mitogenic 
effects rather than tumor incidence data.
    When the mode of action information indicates that the dose-
response function may be adequately described by both a linear and a 
nonlinear approach, then the results of both the linear and the 
nonlinear analyses are presented. An assessment may use both linear and 
nonlinear approaches if different responses are thought to result from 
different modes of action or a response appears to be very different at 
high and low doses due to influence of separate modes of action. The 
results may be needed for assessment of combined risk from agents that 
have common modes of action.
    Absent data to the contrary, the default assumption is that the 
cumulative dose received over a lifetime, expressed as a lifetime 
average daily dose or lifetime average daily exposure, is an 
appropriate measure of dose or exposure. This assumes that a high dose 
of such an agent received over a shorter period of time is equivalent 
to a low dose spread over a lifetime. This is thought to be a 
relatively public-health-protective option and has some empirical 
support (Monro, 1992). A counter example, i.e., effects of short-term, 
high exposure levels that result in subsequent cancer development, is 
treatment of cancer patients with certain chemotherapeutic agents. When 
sufficient information is available to support a different approach, it 
can be used. For example, short-term exposure estimates (several days 
to several months) may be more appropriate than the lifetime average 
daily dose. In these cases, both agent concentration and duration are 
likely to be important, because such effects may be reversible at 
cessation of very short-term exposures.

Appendix B: EPA's Guidance for Data Quality Assessment

    U.S. EPA (U.S. Environmental Protection Agency). (2000d) 
Guidance for data quality assessment: practical methods for data 
analysis. Office of Environmental Information, Washington, DC. EPA/
600/R-96/084. Available from: http://www.epa.gov/quality/qs-docs/g9-final.pdf.

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