The toxicity data of pesticides were summarized and compared amongst different animal species and types of bioassays. These comparisons showed the expected inter-species and inter-bioassay variability. After quantitative and statistical analysis of these data, it was concluded that, on the average, a 2-year dog bioassay detected toxic responses at similar doses as a 2-year rat study, and that both of these bioassays detected toxic responses at lower doses than either a rat 2-generation bioassay, a rat developmental toxicity study, or a 2-year mouse bioassay. Although these chronic dog and rat bioassays were found to detect toxic responses at lower doses than the other studies listed, this analysis does not reflect the seriousness of the effects that were compared. Within the confines of this analysis, then, it appears that a 2-year dog and rat study, reproductive and developmental bioassays are a sufficient data base on which to estimate high confidence Reference Doses (RfDs), and furthermore, that an additional uncertainty factor is needed to estimate RfDs to account for this inter-species and inter-bioassay variability when fewer than this number of bioassays are available.
There are often several data sets that may be used in developing a quantitative risk estimate for a carcinogen. These estimates are usually based, however, on the dose-response data for tumor incidences from a single sex/strain/species of animal. When appropriate, the use of more data should result in a higher level of confidence in the risk estimate. The decision to use more than one data set (e.g., representing different animal sexes, strains, species, or tumor sites) can be made following biological and statistical analyses of the compatibility of the these data sets. Biological analysis involves consideration of factors such as the relevance of the animal models, study design and execution, dose selection and route of administration, the mechanism of action of the agent, its pharmacokinetics, any species- and/or sex-specific effects, and tumor site specificity. If the biological analysis does not prohibit combining data sets, statistical compatibility of the data sets is then investigated. A generalized likelihood ratio test is proposed for determining the compatibility of different data sets with respect to a common dose-response model, such as the linearized multistage model. The biological and statistical factors influencing the decision to combine data sets are described, followed by a case study of bromodichloromethane.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.