Extrapolation from incomplete data to total or lifetime risks at low doses.

Both epidemiology and laboratory data can contribute to estimates of risks to humans of exposure to low doses of carcinogens. The sum of all these contributions does not permit us to make these estimates with certainty. In chronic disease epidemiology, in looking for possible excessive cancer risks, we sometimes fail to have an adequately long observation time or to observe a population sufficiently aged for cancers to appear in meaningful numbers. In studies of most human exposures, dose data are often lacking, beyond a vague "yes-no" or "lots, not much, hardly any." Thus, without a knowledge of what dose produced an observed result it becomes logically impossible to know what result some other (presumed) dose might yield. Animal data show some promise of being useful in extrapolating to low doses in man. However, several problems exist: (a) man is not a tailless, two-legged mouse, or featherless chicken--that is, we do not know if man is more or less sensitive than the laboratory animal; (b) the mathematical model used for extrapolation leads to large differences in estimates of response; (c) man is genetically heterogeneous and is usually exposed to many more hazards than is the laboratory animal. Thus, existing data, even from well-done studies, are inadequate if we want to make extrapolations in any detail or to apply to specific subgroups in the population. Any risk estimation we do may have to be stated in terms that point out the wide ranges of the estimates.