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Updated: Feb 24, 2026

An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
Validation of the prostate health index in a predictive model of prostate cancer
A Sanchís-Bonet1, M Barrionuevo-González2, A M Bajo-Chueca3
1Departamento de Urología, Hospital Universitario Príncipe de Asturias, Alcalá de Henares (Madrid), España.
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×√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.
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