Experimental design constraints on carcinogenic potency estimates.

Abstract

The multistage model is used by U.S. regulatory agencies to calculate estimates of the carcinogenic potency (beta) of chemicals; the data for these estimates are generally obtained from chronic rodent bioassays. Three quantities characterize each group tested in the chronic bioassay: the dose level, the sample size, and the number responding to the dose. The dose levels tested are fixed by conventional protocols; the typical National Toxicology Program (NTP) experimental design calls for use of the maximum tolerated dose (MTD), one-half and one-fourth MTD, plus a control group. Only rarely are doses even one order of magnitude less than the MTD utilized in chronic bioassays. This experimental design constraint on dose selection limits the possible values of beta that can arise from multistage model analyses of chronic bioassay data. Sample size is also constrained by the experimental design of the chronic bioassay; the typical sample size in NTP studies is 50 animals. Occasionally, fewer animals are used, but only rarely are more. Thus, the multistage model which theoretically has three variable quantities with which to estimate carcinogenic potency, has in practice only one: the incidence of treatment-related response. Even this can vary within only a narrow range determined by sample size, the control incidence, and the level of statistical significance desired. The net result of these design constraints is that carcinogenic potency estimates derived from multistage-model analyses of chronic bioassay data may vary within only a narrow range surrounding the inverse maximum dose tested. We have illustrated this by calculating the largest possible finite potency estimates that could have arisen from the experimental designs used to test 82 mouse carcinogens in chronic bioassays. On average these maximum potency estimates were within one order of magnitude of the inverse maximum dose tested. We thus conclude that the chronic rodent bioassay, in and of itself, is altogether inadequate as a data source for estimating the risk to humans from exposure to carcinogenic chemicals.