The Prostate Health Index and multi-parametric MRI improve diagnostic accuracy of detecting prostate cancer in Asian populations

Abstract

PURPOSE: The aim of this study was to evaluate the effectiveness of the Prostate Health Index (PHI) and prostate multi-parametric magnetic resonance imaging (mpMRI) in predicting prostate cancer (PCa) and clinically significant prostate cancer (csPCa) during initial prostate biopsy. MATERIALS AND METHODS: In total, 343 patients underwent initial prostate biopsy and were screened by use of PHI and prostate-specific antigen (PSA) levels between April 2019 and July 2021. A subgroup of 232 patients also underwent prostate mpMRI. Logistic regression analysis was performed to evaluate the accuracies of PSA, PHI, and mpMRI as predictors of PCa or csPCa. These predictive accuracies were quantified by using the area under the receiver operating characteristic curve. The different predictive models were compared using the DeLong test. RESULTS: Logistic regression showed that age, PSA, PHI, and prostate volume were significant predictors of both PCa and csPCa. In the mpMRI subgroup, age, PSA level, PHI, prostate volume, and mpMRI were predictors of both PCa and csPCa. The PHI (area under the curve [AUC]=0.693) was superior to the PSA level (AUC=0.615) as a predictor of PCa (p=0.038). Combining PHI and mpMRI showed the most accurate prediction of both PCa and csPCa (AUC=0.833, 0.881, respectively). CONCLUSIONS: The most accurate prediction of both PCa and csPCa can be performed by combining PHI and mpMRI. In the absence of mpMRI, PHI is superior to PSA alone as a predictor of PCa, and adding PHI to PSA can increase the detection rate of both PCa and csPCa.