A stochastic model of carcinogenesis and tumor size at detection

L. G. Hanin, S. T. Rachev, A. D. Tsodikov, A. Yu Yakovlev

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11 Scopus citations

Abstract

This paper discusses the distribution of tumor size at detection derived within the framework of a new stochastic model of carcinogenesis. This distribution assumes a simple limiting form, with age at detection tending to infinity which is found to be a generalization of the distribution that arises in the length-biased sampling. Two versions of the model are considered with reference to spontaneous and induced carcinogenesis; both of them show similar asymptotic behavior. When the limiting distribution is applied to real data analysis its adequacy can be tested through testing the conditional independence of the size, V, and the age, A, at detection given A > t*, where the value of t* is to be estimated from the given sample. This is illustrated with an application to data on premenopausal breast cancer. The proposed distribution offers the prospect of the estimation of some biologically meaningful parameters descriptive of the temporal organization of tumor latency. An estimate of the model stability to the prior distribution of tumor size and some other stability results for the Bayes formula are given.

Original languageEnglish
Pages (from-to)607-628
Number of pages22
JournalAdvances in Applied Probability
Volume29
Issue number3
DOIs
StatePublished - Sep 1997

Keywords

  • Asymptotic properties
  • Bayes theorem
  • Carcinogenesis
  • Conditional distribution
  • Probability metrics
  • Stability to priors
  • Stochastic model
  • Tumor size

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