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

Objectives: To validate and analyse 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 x root 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. (C) 2017 AEU. Published by Elsevier Espana, S.L.U. All rights reserved.