Screening for prostate cancer by using random-effects models

Larry J. Brant, Shan L. Sheng, Christopher H. Morrell, Geert N. Verbeke, Emmanuel Lesaffre, H. Ballentine Carter

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish (US)
Pages (from-to)51-62
Number of pages12
JournalJournal of the Royal Statistical Society. Series A: Statistics in Society
Volume166
Issue number1
DOIs
StatePublished - 2003

Keywords

  • Cancer diagnosis
  • Classification
  • Disease screening
  • Linear mixed effects model
  • Longitudinal data
  • Prostate-specific antigen

ASJC Scopus subject areas

  • Statistics and Probability
  • Social Sciences (miscellaneous)
  • Economics and Econometrics
  • Statistics, Probability and Uncertainty

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