title: Evaluating batteries of short-term genotoxicity tests.
abstract: Selecting a battery of short-term genotoxicity tests suitable for screening unknown chemicals for carcinogenicity can be a large combinatorial task because of the great number of short-term tests currently available. Biological criteria, such as requirements for different targets and endpoints, can reduce the number of possible combinations. An independent yet potentially complementary approach which we have developed uses Bayes' theorem to predict carcinogenicity from results (positive or negative) in short-term tests. Batteries can be evaluated by their predictivity, calculated with Bayes' theorem from the sensitivities and specificities of the component tests. Our analyses indicate that tests which contribute most to a battery's predictivity are those which are both sensitive and specific, which we call Class I tests. Because few of the currently available tests are Class I, we have extended our analyses to consider when other types of tests must be substituted for Class I tests, the purpose of a particular test program will influence the choice. In order to obtain the best predictions for all chemicals, a battery should include an equal number of Class II tests (i.e. those that are sensitive but are not specific) and Class III tests (i.e. those that are not sensitive but are specific). However, for the purpose of reducing the number of carcinogens erroneously classified as non-carcinogenic, Class II tests contribute about twice as much to the predictivity of a battery as do Class III tests, and for the purpose of reducing the number of non-carcinogens erroneously classified as carcinogenic, Class II tests contribute about half as much as Class III tests.(ABSTRACT TRUNCATED AT 250 WORDS)
authors.affiliation: Department of Environmental Health Sciences, Case Western Reserve University, School of Medicine, Cleveland, OH 44106.
authors.forename: F K
authors.initials: FK
authors.lastname: Ennever
authors.forename: H S
authors.initials: HS
authors.lastname: Rosenkranz
mesh_terms: D009152:Mutagenicity Tests; D011237:Predictive Value of Tests; D011336:Probability