Screening for prostate cancer by using random-effects models
Random-effects models are used to screen male participants in a long-term longitudinal study for prostate cancer. By using posterior probabilities, each male can be classified into one of four diagnostic states for prostate disease: normal, benign prostatic hyperplasia, local cancer and metastatic cancer. Repeated measurements of prostate-specific antigen, collected when there was no clinical evidence of prostate disease, are used in the classification process. An individual's screening data are considered one repeated measurement at a time as his data are collected longitudinally over time. Posterior probabilities are calculated on the basis of data from other individuals with confirmed diagnoses of each of the four diagnostic states.
Document Type: Research Article
Affiliations: 1: National Institute on Aging, Baltimore, USA 2: National Institute on Aging, Baltimore, and Loyola College, Baltimore, USA 3: Katholieke Universiteit Leuven, Belgium 4: Johns Hopkins University School of Medicine, Baltimore, USA
Publication date: 2003-02-01