Abstract
Background
The emergence of genomic precision oncology has advanced personalized care for some patients with prostate cancer (PCa), while threatening to widen existing disparities due to the historically low recruitment of African American men (AAM), who have the highest disease burden. Here, we report the first prospective validation of a genomic classifier (GC) to predict rapid-onset biochemical recurrence (BCR) in AAM.
Methods
Between 2016 and 2021, this multicenter prospective validation study recruited 243 patients with low- or intermediate-risk PCa who received treatment for their disease. Patients were recruited on a 1:1 basis (AAM:White) and matched by CAPRA score. Patients who elected active surveillance were ineligible for participation. Decipher GC testing was ordered for all patients using their biopsy and/or radical prostatectomy (RP) tumor tissue. The primary outcome was to determine whether the GC could predict 2-year BCR rates—used as a surrogate for disease aggressiveness—following standard treatment. The secondary outcome evaluated the concordance between biopsy- and RP-derived GC risk scores for treatment recommendations.
Results
The final analytical cohort included 226 matched patients with genomic information, and 207 evaluable cases (104 AAM, 103 White) with both genomic and complete clinical outcome data. Overall, a high genomic-risk GC score was associated with a 5.25-fold increase in the odds of rapid-onset 2-year BCR compared with the low-risk group (odds ratio, 5.25 [95% CI, 1.27–21.66]; P =.021). In a subset of the surgical cohort (n=74), biopsy- and RP-derived GC scores exhibited a 77% concordance rate, defined as no reclassification in GC risk-based categories.
Conclusions
This study represents the first prospective validation of GC performance in predicting early 2-year BCR in both AAM and White men. The findings provide strong evidence supporting the integration of the GC into clinical practice guidelines to improve risk stratification and management of AAM with early-stage PCa.
ClinicalTrials.gov identifier: NCT02723734