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To evaluate the performance of the Prostate Health Index (PHI) in magnetic resonance imaging-transrectal ultrasound (MRI-TRUS) fusion prostate biopsy for the detection of clinically significant prostate cancer (csPCa). We prospectively enrolled 164 patients with at least one Prostate Imaging Reporting and Data System version 2 (PI-RADS v2) ≥ 3 lesions who underwent MRI-TRUS fusion prostate biopsy. Of the PSA-derived biomarkers, the PHI had the best performance in predicting csPCa (AUC 0.792, CI 0.707-0.877) in patients with PI-RADS 4/5 lesions. Furthermore, the predictive power of PHI was even higher in the patients with PI-RADS 3 lesions (AUC 0.884, CI 0.792-0.976). To minimize missing csPCa, we used a PHI cutoff of 27 and 7.4% of patients with PI-RADS 4/5 lesions could have avoided a biopsy. At this level, 2.0% of cases with csPCa would have been missed, with sensitivity and NPV rates of 98.0% and 87.5%, respectively. However, the subgroup of PI-RADS 3 was too small to define the optimal PHI cutoff. PHI was the best PSA-derived biomarker to predict csPCa in MRI-TRUS fusion prostate biopsies in men with PI-RADS ≥ 3 lesions, especially for the patients with PI-RADS 3 lesions who gained the most value.

Background: In patients undergoing radical prostatectomy (RP) for prostate cancer (PCa), preoperative prediction of extraprostatic extension (EPE) can facilitate patient selection for nerve-sparing procedures. Since both multiparametric magnetic resonance imaging (mpMRI) and prostate health index (PHI) have shown promise for the diagnosis and prognostication of PCa, we investigated whether a combination of mpMRI and PHI evaluations can improve the prediction of EPE after RP. Methods: Patients diagnosed with PCa and treated with RP were prospectively enrolled between February 2017 and July 2019. Preoperative blood samples were analyzed for PHI (defined as [p2PSA/fPSA] × vtPSA), and mpMRI examinations were performed and interpreted by a single experienced uroradiologist retrospectively. The area under the receiver operating characteristic curve (ROC) was used to determine the performance of mpMRI, PHI, and their combination in predicting EPE after RP. Results: A total of 163 patients were included for analysis. The pathological T stage was T3a or more in 59.5%. Overall staging accuracy of mpMRI for EPE was 72.4% (sensitivity and specificity: 73.2% and 71.2%, respectively). The area under the ROC of the combination of mpMRI and PHI in predicting EPE (0.785) was higher than those of mpMRI alone (0.717; p = 0.0007) and PHI alone (0.722; p = 0.0236). mpMRI showed false-negative non-EPE results in 26 patients (16%), and a PHI threshold of >40 could avoid undiagnosed EPE before RP in 21 of these 26 patients. Conclusion: The combination of PHI and mpMRI may better predict the EPE preoperatively, facilitating preoperative counseling and tailoring the need for nerve-sparing RP. [ABSTRACT FROM AUTHOR]