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Background: There are models to predict pathological outcomes based on established clinical and prostate-specific antigen (PSA)-derived parameters; however, they are not satisfactory. p2PSA and its derived biomarkers have shown promise for the diagnosis and prognosis of prostate cancer (PCa). The aim of this study was to investigate whether p2PSA-derived biomarkers can assist in the prediction of aggressive pathological outcomes after radical prostatectomy (RP)., Methods: We prospectively enrolled patients who were diagnosed with PCa and treated with RP between February 2017 and December 2018. Preoperative blood samples were analyzed for tPSA, free PSA (fPSA), percentage of fPSA (%fPSA), [-2]proPSA (p2PSA), and percentage of p2PSA (%p2PSA). Prostate health index (PHI) was calculated as (p2PSA/fPSA) × √tPSA. Prostate volume was determined by transrectal ultrasound using the ellipsoid formula, and PHI density was calculated as PHI/prostate volume. The areas under the receiver operating characteristic curve were estimated for various PSA/p2PSA derivatives. Aggressive pathological outcomes measured after RP were defined as pathological T3 or a Gleason score (GS) >6 as determined in RP specimens., Results: One hundred and forty-four patients were included for analysis. Postoperative GS was >6 in 86.1% of the patients, and pT stage was T3a or more in 54.2%. Among all PSA- and p2PSA-derived biomarkers, PHI density was the best biomarker to predict aggressive pathological outcomes after RP. The odds ratio of having an aggressive pathological outcome of RP was 8.796 (p = 0.001). In multivariate analysis, adding %fPSA to base model did not improve the accuracy (area under curve), but adding PHI and PHI density to base model improved the accuracy by 2% and 16%, respectively, in predicting pT3 stage or GS ≥ 7. The risk of pT3 stage or GS ≥ 7 was 20.8% for PHI density <1.125, and 64.6% for PHI density >1.125 (sensitivity: 74.6% and specificity: 88.9%)., Conclusion: PHI density may further aid in predicting aggressive pathological outcomes after RP. This biomarker may be useful in preoperative counseling and may have potential in decision making when choosing between definitive treatment and active surveillance of newly diagnosed PCa.

Background: Few prospective studies have focused on the performance of the Prostate Health Index (PHI) in Asian populations. Therefore, we aimed to evaluate the performance of the PHI in predicting prostate cancer (PCa) compared with standard prostate-specific antigen (PSA) tests., Methods: We prospectively enrolled patients with suspected PCa with a total PSA (tPSA) level 4 to 10 ng/mL or tPSA <4 ng/mL and a suspicious digital rectal examination between February 2017 and September 2018. All of the patients underwent a 12-core transrectal ultrasound-guided prostate biopsy. Prebiopsy blood samples were analyzed for tPSA, free PSA (fPSA), percentage of fPSA (%fPSA), [-2]proPSA (p2PSA), and percentage of p2PSA (%p2PSA). The PHI was calculated as (p2PSA/fPSA) × √tPSA. The areas under the receiver operating characteristic curve (AUCs) were estimated for the PSA derivatives in addition to their specificities at a prespecified sensitivity of 90%., Results: Of the 307 enrolled patients, 95 (30.9%) had PCa on biopsy. Excluding fPSA, all of the PSA derivatives were significantly different between the positive and negative biopsy groups. Of the various derivatives, the PHI (AUC: 0.783) showed the best performance in predicting the results of the initial biopsy compared with tPSA (AUC: 0.611). At a sensitivity of 90%, the PHI had the best specificity of 46.7% compared with 23.2% for tPSA. Using a PHI cutoff value of 35.15 for biopsy, 108 (35.2%) patients could have avoided undergoing a biopsy. To detect Gleason score ≥ 7 disease at 90% sensitivity, the threshold for PHI was 36.96 with a specificity of 52.1%., Conclusion: PHI was the best biomarker among the PSA derivatives in predicting PCa at biopsy in men with tPSA < 10 ng/mL. The risk of a Gleason score ≥ 7 increased with increasing PHI.

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]