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Titolo:
Using short-term tests to predict carcinogenic activity in the long-term bioassay
Autore:
Kodell, RL; Chen, JJ; Jackson, CD; Gaylor, DW;
Indirizzi:
US FDA, Div Biometry & Risk Assessment, Natl Ctr Toxicol Res, Jefferson, AR US FDA Jefferson AR USA 72079 ssment, Natl Ctr Toxicol Res, Jefferson, AR USARDA, Off Risk Assessment Policy & Res, Natl Ctr Toxicol Res, Jefferson,US FDA Jefferson AR USA 72079 icy & Res, Natl Ctr Toxicol Res, Jefferson,
Titolo Testata:
HUMAN AND ECOLOGICAL RISK ASSESSMENT
fascicolo: 2, volume: 5, anno: 1999,
pagine: 427 - 443
SICI:
1080-7039(199904)5:2<427:USTTPC>2.0.ZU;2-6
Fonte:
ISI
Lingua:
ENG
Soggetto:
NATIONAL TOXICOLOGY PROGRAM; CHEMICAL-STRUCTURE; SALMONELLA ASSAY; LIVER; PROLIFERATION; MUTAGENICITY; RODENTS; ABILITY; MODEL;
Keywords:
Ames test; logistic regression; classification; positive predictivity; negative predictivity;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Agriculture,Biology & Environmental Sciences
Citazioni:
26
Recensione:
Indirizzi per estratti:
Indirizzo: Kodell, RL US FDA, Div Biometry & Risk Assessment, Natl Ctr Toxicol Res, 3900 NCTR Rd, US FDA 3900 NCTR Rd Jefferson AR USA 72079 l Res, 3900 NCTR Rd,
Citazione:
R.L. Kodell et al., "Using short-term tests to predict carcinogenic activity in the long-term bioassay", HUM ECOL R, 5(2), 1999, pp. 427-443

Abstract

A method for classifying chemicals with respect to carcinogenic potential based on short-term test results is presented. The method utilizes the logistic regression model to translate results from short-term toxicity assays into predictions of the likelihood that a chemical will be carcinogenic if tested in a long-term bioassay. The proposed method differs from previous approaches in two ways. First, statistical confidence limits on probabilities of cancer rather than central estimates of those probabilities are used for classification. Second, the method does not classify all chemicals in a data base with respect to carcinogenic potential. Instead, it identifies chemicals with highest and lowest likelihood of testing positive for carcinogenicity in the bioassay. A subset of chemicals with intermediate likelihoodof being positive remains unclassified, and will require further testing, perhaps in a long-term bioassay. Two data bases of binary short-term and long-term test results from the literature are used to illustrate and evaluate the proposed procedure. A cross-validation analysis of one of the data sets suggests that, for a sufficiently rich data base of chemicals, the development of a robust predictive system to replace the bioassay for some unknown chemicals is a realistic goal.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 21/09/20 alle ore 10:53:11