title: Predictive probability of serum prostate-specific antigen for prostate cancer: an approach using Bayes rule.
abstract: This article introduces the use of Bayes probability rule to calculate age and serum prostate-specific antigen (PSA)-specific positive predictive values (PPVs) for prostate cancer. The PPV is the conditional probability of having prostate cancer, given a value of PSA and a particular age group. The formulation uses values of sensitivity obtained from previously reported studies of more than 2,700 men with prostate cancer, and it uses values of specificity obtained from previously reported studies of more than 99,000 men without prostate cancer. The formulation also introduces the use of a population-based and age-specific probability of prostate cancer, and for this it relies on the National Cancer Institute-sponsored Surveillance, Epidemiology and End Results data. The Bayes PPV suggests that in younger men, cut points defining an elevated PSA level should be raised rather than lowered. The Bayes formulation also provides estimates of the PPV for narrow intervals of PSA, and these tabulated results may provide useful guidelines for the implications of serum PSA levels at specific age groups.
authors.affiliation: Department of Laboratory Medicine, Veterans Affairs Medical Center, Durham, NC 27705, USA.
authors.forename: Robin T
authors.initials: RT
authors.lastname: Vollmer
mesh_terms: D000230:Adenocarcinoma / Q000097:blood / Q000175:diagnosis*; D000368:Aged; D001499:Bayes Theorem; D023381:Endpoint Determination / Q000706:statistics & numerical data; D006801:Humans; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D017430:Prostate-Specific Antigen / Q000097:blood*; D011471:Prostatic Neoplasms / Q000097:blood / Q000175:diagnosis*
chemical_list: D017430:Prostate-Specific Antigen