Early favorable prostate-specific antigen response prediction in metastatic hormone sensitive prostate cancer.

Abstract

There is an unmet need for a tool that could predict early favorable prostate-specific antigen (PSA) response in metastatic hormone sensitive prostate cancer (mHSPC) patients receiving androgen receptor pathway inhibitor (ARPI). Here, we train and validate a multivariable logistic regression model to predict early favorable PSA response (≤0.2 ng/mL by 6 months) in these patients. Patients randomly allocated to the ARPI arms of the LATITUDE (abiraterone), TITAN (apalutamide), and ARASENS (darolutamide) trials, are split 60:40 into training (n = 1030) and internal validation (n = 688) cohorts. The locked model is validated in an independent external validation cohort - the enzalutamide arm of the ENZAMET trial (n = 540). The area under curve and Brier score for the locked model in the external validation cohort are 0.82 (95% confidence interval [CI] = 0.78-0.85) and 0.16, respectively. Stratification by predicted probability tertiles show PSA response rates of 92% (95% CI = 88-96), 74% (95% CI = 68-81), and 39% (95% CI = 32-47), respectively. Pending prospective validation, our model predicts early favorable PSA response supporting its potential role in guiding treatment decisions.