Abstract

To construct a pre-biopsy predictive model incorporating several clinical variables, including African-American (AA) or Caucasian race, to predict the risk of prostate cancer detection on prostate biopsy, as traditionally AA men have had a higher incidence of prostate cancer than Caucasian men, but previous predictive tools for prostate cancer have not incorporated the effect of race. We evaluated 9473 patients undergoing initial prostate biopsy at three equal-access healthcare institutes from 1993 to 2003. At each biopsy session, patient age, race, serum prostate-specific antigen level (PSA), digital rectal examination (DRE) findings, number of biopsy cores taken, year of biopsy, and pathological findings were recorded. A logistic regression model was constructed to evaluate predictors of cancer detection based on pre-biopsy variables. The model was internally validated using the bootstrap statistical method, and a nomogram was constructed. Prostate cancer was diagnosed in 1895 (33%) AA men and 991 (26%) Caucasians. AA men had a significantly higher mean serum PSA level than Caucasians, at 13.0 and 8.5 ng/mL, respectively (P < 0.001). The mean ages were similar between AA and Caucasian men (P = 0.23), but Caucasian men had a higher incidence of an abnormal DRE (P < 0.001). On multivariate analysis, age, race, year of biopsy, PSA level, DRE, and number of cores taken were all statistically significant (P < 0.001). Hazard ratios were (controlling for year of biopsy); age (1.30), Caucasian race (0.74), PSA level (1.47), DRE (1.75), and number of cores taken (1.19). The predicted model had a boot-strapped concordance index of 0.75. AA race remains an independent predictor of prostate cancer detection in men undergoing initial prostate biopsy. This nomogram is the first to individualise the risk by AA or Caucasian race in a predictive model for counselling men on their probability of having cancer at the time of their first biopsy.

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