African-American race is a predictor of prostate cancer detection: incorporation into a pre-biopsy nomogram.
Academic Article
Overview
abstract
OBJECTIVES: 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. PATIENTS AND METHODS: 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. RESULTS: 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. CONCLUSION: 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.
