title: Two-stage models for the analysis of cancer screening data.
abstract: Methods are proposed for the analysis of the natural history of disease from screening data when it cannot be assumed that untreated preclinical disease always progresses to clinical disease. The methodology is based on a two-stage model for preclinical disease in which stage 1 lesions may or may not progress to stage 2, but all stage 2 lesions progress to clinical disease. The focus is on joint estimation of the total preclinical duration and the sensitivity of the screening test. A partial likelihood is proposed for the analysis of prospectively collected screening data, and an analogous conditional likelihood is proposed for retrospective data. Some special cases for the joint sojourn distribution of the two stages are considered, including the independent model and limiting models where the duration of stage 2 is short relative to stage 1. The methods are applied to a case-control study of cervical cancer screening in Northeast Scotland.
authors: Johns Hopkins University, Department of Biostatistics, Baltimore, Maryland 21205.
authors: R
authors: R
authors: Brookmeyer
authors: N E
authors: NE
authors: Day
mesh_terms: D001699:Biometry; D005260:Female; D006801:Humans; D008403:Mass Screening; D008962:Models, Theoretical; D009369:Neoplasms / Q000175:diagnosis* / Q000517:prevention & control; D011446:Prospective Studies; D012606:Scotland; D002583:Uterine Cervical Neoplasms / Q000175:diagnosis*