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 language | English (US) |
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Pages (from-to) | 1056-1063 |
Number of pages | 8 |
Journal | Biometrics |
Volume | 61 |
Issue number | 4 |
DOIs | |
State | Published - Dec 2005 |
Externally published | Yes |
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
- General Biochemistry, Genetics and Molecular Biology
- General Immunology and Microbiology
- General Agricultural and Biological Sciences
- Applied Mathematics