The London Principles for Evaluating Epidemiologic Data in Regulatory Risk Assessment

Part B. Principles for Using Human and Animal Data in Dose-Response Evaluation

PREAMBLE

Proceeding to application of the dose-response principles assumes that the existence of a hazard has been adequately established under the above principles. On the other hand, adequate establishment of hazard, even with a showing of strong and consistent association, does not necessarily mean there are sufficient data for use in dose-response evaluation. The dose-response principles assume that there is a need for dose-response extrapolation because no individual epidemiologic study provides sufficient high-quality information on dose-response to reach conclusions about dose-response at the exposure levels being addressed in the regulatory risk assessment.

These principles also assume that higher quality data are required for dose-response evaluation than for hazard identification, and that data used for dose-response should meet some minimum standards or quality hurdles. In other words, the reviewer and risk assessor should answer the basic question of whether the epidemiologic data, in an individual study or cumulatively, are adequate for use in dose-response evaluation. There is no formula or quantitative weighting scheme prescribed for making this judgment.

The principles address not only the use of epidemiologic data by themselves, but also their use in combination or conjunction with animal and/or biologic data. Consequently, there is an even greater need than in the hazard identification phase for scientists from relevant disciplines other than epidemiology to work with the risk assessor to interpret the data.

If epidemiologic data adequate for dose-response evaluation are not available, and a risk assessment is being developed for use in making an important regulatory decision, and if it is feasible to develop new epidemiologic data, or to extract new data from existing studies, an effort should be made to develop and provide good epidemiologic dose-response data that can be used together with, or in preference to, high-dose animal data.

Principle B-1.
Dose-response assessment should include a range of reasonable dose measures, explain why any were rejected, and provide a rationale if any particular dose metric is preferred. In evaluations of both human and animal data, several different measures of dose should be evaluated (if possible).

Principle B-2.
In the selection of a dose-response model, the greatest weight should be given to models that fit the observed animal and human data and are consistent with the biologically relevant mode(s) of action (genotoxic, nongenotoxic, unclassified). When mechanistic knowledge is uncertain or limited, several plausible dose-response models should be considered and the most plausible ones, based on available data and professional judgment, should generally be used in dose-response evaluation.

Principle B-3.
When extrapolating cancer risk to exposure levels below the observable range, mechanistic data should be used to characterize the shape of the dose-response function.

Principle B-4.
When the available epidemiologic data are not adequate to perform dose-response analyses, causing low-dose estimates of risk to be derived exclusively from animal data, every effort should still be made to use the available human data in assessing the validity of low-dose risk estimates. To the extent feasible, heterogeneity in the human population should be accounted for. Whenever feasible, human data on metabolic biomarkers and other biological measures should be employed to adjust the risk estimates for known differences between species and between high and low doses. If possible, data on susceptibility should be included.

Principle B-5.
When epidemiologic studies are selected for dose-response assessment, higher quality studies should be given preference, especially those with precise and accurate exposure information. The availability of information with respect to timing of exposure and response (time/age of first exposure, intensity of exposure, time to tumor), adjustment for confounding variables, and potential interaction with other effect modifiers is particularly important.

Principle B-6.
A properly conducted meta-analysis, or preferably an analysis based on the raw data in the original studies, may be used in hazard identification and dose-response evaluation when such combination includes an evaluation of individual studies and an assessment of heterogeneity. The combined results ought to provide, more than any single study, precise risk estimates over a wider range of doses. Before using these tools, the gains should be judged sufficient to justify potential errors in inference resulting from combining studies of dissimilar design and quality.

Principle B-7.
When epidemiological data are used in dose-response assessment, a quantitative sensitivity analysis should be conducted to determine the potential effects on risk estimates of confounders, measurement error, and other sources of uncontrolled bias in study design.

Principle B-8.
Scientific understanding of differentials in human susceptibility to disease (racial/ethnic/gender/genetic differences, genetic polymorphisms, etc.) should be used to refine the low-dose extrapolation procedures when such phenomena are adequately understood.

Principle B-9.
To characterize the most important sources of uncertainty in the final estimate of risk, a quantitative analysis should be conducted to determine the major sources of uncertainty in dose-response assessment, including discussion of the prospects that future research might diminish the various sources of uncertainties.

EPILOGUE TO PRINCIPLES:
Questioning of epidemiologist researchers by risk assessors

1. Risk assessors' criticisms and major questions about the methods, analyses, data, or interpretation of a published report should be directed, whenever possible, to the epidemiologist(s) responsible for the paper, and they should be given an opportunity to respond.
2. Risk assessors may want access to the study's data set for other analyses to be used in the risk assessment. This would be done with the consent and cooperation of the study epidemiologist(s).

RECOMMENDATIONS FOR IMPROVING FUTURE
EPIDEMIOLOGIC STUDIES AND THEIR USE IN
REGULATORY RISK ASSESSMENT

Recommendation 1.
A commitment to collaboration should be made by epidemiologists and risk assessors that includes (a) sharing of raw data where feasible, (b) exchange of protocols and survey instruments, (c) inclusion of epidemiologists in dose-response modeling exercises, and (d) care and fairness by risk assessors in the critique of original epidemiologic studies.

Recommendation 2.
Future epidemiologic studies should be funded and designed with the needs of regulatory risk assessors in mind, including (a) richer exposure information (e.g., age-specific exposure histories and measures of key confounders), and (b) ample resources for careful dose-response analyses.

Recommendation 3.
Epidemiologic study teams (and the peer review panels that evaluate them for funding) should include multidisciplinary expertise from the fields of medicine, toxicology, industrial hygiene, statistics, and risk assessment, as well as epidemiology.

Recommendation 4.
Peer review should be applied to the use of epidemiologic data in risk assessment, including (a) involvement of the original epidemiologic investigator(s) when possible, (b) panels that reflect stature, objectivity, appropriate areas of expertise, and balance in perspective, and (c) opportunity for public comment, such as that used by EPA's Science Advisory Board.

Recommendation 5.
Reporting of epidemiologic findings should be responsive, if possible, to the needs of risk assessors, including (a) documentation of rationales for decisions about how data were grouped for analysis purposes, (b) clear distinctions between subjects with small vs. zero exposure, and (c) reporting of extent of pre-testing in multivariate modeling in order to allow better interpretation of classical statistical tests.