The effect of race on the discriminatory accuracy of models to predict biochemical recurrence after radical prostatectomy: results from the Shared Equal Access Regional Cancer Hospital and Duke Prostate Center databases

Abstract

To evaluate whether race modifies the accuracy of nomograms to predict biochemical recurrence (BCR) after radical prostatectomy among subjects from the Shared Equal Access Regional Cancer Hospital (SEARCH) and Duke Prostate Center (DPC) databases. Retrospective analysis of 1721 and 4511 subjects from the SEARCH and DPC cohorts, respectively. The discrimination accuracy for BCR of seven previously published predictive models was assessed using concordance index and compared between African-American men (AAM) and Caucasian men (CM). AAM represented 44% of SEARCH and 14% of DPC. In both cohorts, AAM were more likely to experience BCR than CM (P<0.01). In SEARCH, the mean concordance index across all seven models was lower in AAM (0.678) than CM (0.715), though the mean difference between CM and AAM was modest (0.037; range 0.015-0.062). In DPC the overall mean concordance index for BCR across all seven nomograms was 0.686. In contrast to SEARCH, the mean concordance index in DPC was higher in AAM (0.717) than CM (0.681), though the mean differences between CM and AAM was modest (-0.036; range -0.078 to -0.004). Across all seven models for predicting BCR, the discriminatory accuracy was better among CM in SEARCH and better among AAM in DPC. The mean difference in discriminatory accuracy of all seven nomograms between AAM and CM was approximately 3-4%. This indicates that currently used predictive models have similar performances among CM and AAM. Therefore, nomograms represent a valid and accurate method to predict BCR regardless of race.