MLE and Bayesian inference of age-dependent sensitivity and transition probability in periodic screening

Dongfeng Wu, Gary L. Rosner, Lyle Broemeling

Research output: Contribution to journalArticlepeer-review

Abstract

This article extends previous probability models for periodic breast cancer screening examinations. The specific aim is to provide statistical inference for age dependence of sensitivity and the transition probability from the disease free to the preclinical state. The setting is a periodic screening program in which a cohort of initially asymptomatic women undergo a sequence of breast cancer screening exams. We use age as a covariate in the estimation of screening sensitivity and the transition probability simultaneously, both from a frequentist point of view and within a Bayesian framework. We apply our method to the Health Insurance Plan of Greater New York study of female breast cancer and give age-dependent sensitivity and transition probability density estimates. The inferential methodology we develop is also applicable when analyzing studies of modalities for early detection of other types of progressive chronic diseases.

Original languageEnglish (US)
Pages (from-to)1056-1063
Number of pages8
JournalBiometrics
Volume61
Issue number4
DOIs
StatePublished - Dec 2005
Externally publishedYes

Keywords

  • Bayesian analysis
  • Breast cancer
  • Early detection
  • Markov chain Monte Carlo
  • Periodic screening
  • Sensitivity
  • Sojourn time
  • Transition probability

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry, Genetics and Molecular Biology(all)
  • Immunology and Microbiology(all)
  • Agricultural and Biological Sciences(all)
  • Applied Mathematics

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