Assessing prostate cancer risk: Results from the prostate cancer prevention trial

Abstract

Background: Prostate-specifi c antigen (PSA) testing is the pri-mary method used to diagnose prostate cancer in the United States. Methods to integrate other risk factors associated with prostate cancer into individualized risk prediction are needed. We used prostate biopsy data from men who par ticipated in the Prostate Cancer Prevention Trial (PCPT) to develop a predictive model of prostate cancer. Methods: We included 5519 men from the placebo group of the PCPT who under-went prostate biopsy, had at least one PSA measurement and a digital rectal examination (DRE) performed during the year before the biopsy, and had at least two PSA measurements performed during the 3 years before the prostate biopsy. Logistic regression was used to model the risk of prostate can-cer and high-grade disease associated with age at biopsy, race, family history of prostate cancer, PSA level, PSA velocity, DR