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Title: Characterizing dose-response relationships in multiple cancer bioassays.

Authors: French, J L; Williams, P L

Published In Risk Anal, (2001 Feb)

Abstract: In the evaluation of chemical compounds for carcinogenic risk, regulatory agencies such as the U.S. Environmental Protection Agency and National Toxicology Program (NTP) have traditionally fit a dose-response model to data from rodent bioassays, and then used the fitted model to estimate a Virtually Safe Dose or the dose corresponding to a very small increase (usually 10(-6)) in risk over background. Much recent interest has been directed at incorporating additional scientific information regarding the properties of the specific chemical under investigation into the risk assessment process, including biological mechanisms of cancer induction, metabolic pathways, and chemical structure and activity. Despite the fact that regulatory agencies are currently poised to allow use of nonlinear dose-response models based on the concept of an underlying threshold for nongenotoxic chemicals, there have been few attempts to investigate the overall relationship between the shape of dose-response curves and mutagenicity. Using data from an historical database of NTP cancer bioassays, the authors conducted a repeated-measures Analysis of the estimated shape from fitting extended Weibull dose-response curves. It was concluded that genotoxic chemicals have dose-response curves that are closer to linear than those for nongenotoxic chemicals, though on average, both types of compounds have dose-response curves that are convex and the effect of genotoxicity is small.

PubMed ID: 11332555 Exiting the NIEHS site

MeSH Terms: Animals; Biological Assay/methods; Biological Assay/statistics & numerical data; Carcinogenicity Tests/methods; Carcinogenicity Tests/statistics & numerical data; Carcinogens/administration & dosage*; Carcinogens/toxicity*; Databases, Factual; Dose-Response Relationship, Drug; Female; Humans; Male; Mice; Mutagens/administration & dosage; Mutagens/toxicity; Nonlinear Dynamics; Rats; Risk Assessment/methods*; Risk Assessment/statistics & numerical data

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