Testing goodness of fit for stochastic models of carcinogenesis.
This paper considers the utility of statistical goodness of fit testing in the context of mechanistic models of carcinogenesis. Two stochastic models of carcinogenesis were tested with several sets of experimental and epidemiological data using a formal goodness of fit test specially designed to accommodate censored observations: these were the two-stage model allowing for clonal expansion of initiated cells and its simpler version with gamma distributed promotion time. The results of this application, supplemented by visual examination of local likelihood kernel estimates of the hazard function and the corresponding model-based estimates, show that mechanistic models of carcinogenesis provide a good fit to the data in the majority of cases under study.
Gregori
Giovanni
G
Department of Oncological Sciences, Division of Biostatistics, Huntsman Cancer Institute, University of Utah, 2000 Circle of Hope, Salt Lake City, UT 84112, USA. ggregori@hci.utah.edu
Hanin
Leonid
L
Luebeck
Georg
G
Moolgavkar
Suresh
S
Yakovlev
Andrei
A
D000818:Animals; D015197:Carcinogenicity Tests; D005260:Female; D006801:Humans; D016013:Likelihood Functions; D008297:Male; D051379:Mice; D008954:Models, Biological; D009369:Neoplasms / Q000139:chemically induced / Q000209:etiology*; D051381:Rats; D017208:Rats, Wistar; D013269:Stochastic Processes