Validation of the prostate health index in a predictive model of prostate cancer

Abstract Objectives To validate and analyze the clinical usefulness of a predictive model of prostate cancer that incorporates the biomarker “[-2] pro prostate-specific antigen” using the prostate health index (PHI) in decision making for performing prostate biopsies. Material and methods We isolated serum from 197 men with an indication for prostate biopsy to determine the total prostate-specific antigen (tPSA), the free PSA fraction (fPSA) and the [-2] proPSA (p2PSA). The PHI was calculated as p2PSA/fPSA × √tPSA. We created 2 predictive models that incorporated clinical variables along with tPSA or PHI. The performance of PHI was assessed with a discriminant analysis using receiver operating characteristic curves, internal calibration and decision curves. Results The areas under the curve for the tPSA and PHI models were 0.71 and 0.85, respectively. The PHI model showed a better ability to discriminate and better calibration for predicting prostate cancer but not for predicting a Gleason score in the biopsy ≥7. The decision curves showed a greater net benefit with the PHI model for diagnosing prostate cancer when the probability threshold was 15–35% and greater savings (20%) in the number of biopsies. Conclusions The incorporation of p2PSA through PHI in predictive models of prostate cancer improves the accuracy of the risk stratification and helps in the decision-making process for performing prostate biopsies.