Biomaterial Database

Applicability of alternative models of revertant variance to Ames-test data for 121 mutagenic carcinogens. 1994

K T Bogen

Health and Ecological Assessment Div., Lawrence Livermore National Laboratory, CA 94550-9900.

Models of sampling variance in replicate revertant scores play a role in analyses of Ames-test data on mutagenicity in Salmonella, both in modeling the dose-response relation and in estimating initial dose-response slope or 'potency', e.g., for use in correlating mutagenic and carcinogenic potencies among different chemicals. Both generalized Poisson (GP) and negative binomial (NB) models of revertant variance have been applied in this way, but their empirical applicability has only been assessed using Ames-test data on a few chemicals. The applicability of these and related variance models was therefore assessed for 1905 such data sets pertaining to 121 putatively mutagenic carcinogens. Only approximately 50% of the data sets analyzed were found to involve a significantly positively correlated dose-response, and < 50% were found to exhibit a plausibly heterogeneous response variance regardless of dose-response correlation. Among data sets with plausibly heterogeneous variance, < 60% were found to exhibit significantly extra-Poisson variability. Among the significantly extra-Poisson data sets, most (> 75% among dose-response correlated data sets) were found to exhibit revertant variance consistent with both the GP and NB models; while the GP model was found to be somewhat more consistent with these data, the NB model more often gave a nominally better fit when both models were consistent. Implications of these results for the design of methods used to analyze Ames-test data are discussed.

UI	MeSH Term	Description	Entries
D009152	Mutagenicity Tests	Tests of chemical substances and physical agents for mutagenic potential. They include microbial, insect, mammalian cell, and whole animal tests.	Genetic Toxicity Tests,Genotoxicity Tests,Mutagen Screening,Tests, Genetic Toxicity,Toxicity Tests, Genetic,Genetic Toxicity Test,Genotoxicity Test,Mutagen Screenings,Mutagenicity Test,Screening, Mutagen,Screenings, Mutagen,Test, Genotoxicity,Tests, Genotoxicity,Toxicity Test, Genetic
D009153	Mutagens	Chemical agents that increase the rate of genetic mutation by interfering with the function of nucleic acids. A clastogen is a specific mutagen that causes breaks in chromosomes.	Clastogen,Clastogens,Genotoxin,Genotoxins,Mutagen
D002273	Carcinogens	Substances that increase the risk of NEOPLASMS in humans or animals. Both genotoxic chemicals, which affect DNA directly, and nongenotoxic chemicals, which induce neoplasms by other mechanism, are included.	Carcinogen,Oncogen,Oncogens,Tumor Initiator,Tumor Initiators,Tumor Promoter,Tumor Promoters,Initiator, Tumor,Initiators, Tumor,Promoter, Tumor,Promoters, Tumor
D012475	Salmonella	A genus of gram-negative, facultatively anaerobic, rod-shaped bacteria that utilizes citrate as a sole carbon source. It is pathogenic for humans, causing enteric fevers, gastroenteritis, and bacteremia. Food poisoning is the most common clinical manifestation. Organisms within this genus are separated on the basis of antigenic characteristics, sugar fermentation patterns, and bacteriophage susceptibility.
D015233	Models, Statistical	Statistical formulations or analyses which, when applied to data and found to fit the data, are then used to verify the assumptions and parameters used in the analysis. Examples of statistical models are the linear model, binomial model, polynomial model, two-parameter model, etc.	Probabilistic Models,Statistical Models,Two-Parameter Models,Model, Statistical,Models, Binomial,Models, Polynomial,Statistical Model,Binomial Model,Binomial Models,Model, Binomial,Model, Polynomial,Model, Probabilistic,Model, Two-Parameter,Models, Probabilistic,Models, Two-Parameter,Polynomial Model,Polynomial Models,Probabilistic Model,Two Parameter Models,Two-Parameter Model