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Introduction and Objectives: To evaluate the association between metabolic syndrome (MetS) and proliferative inflammatory atrophy (PIA) in patients with suspected prostate cancer (PCa)., Patients and Methods: From June 2015 to July 2016, we conducted the FIERY (Flogosis Increased Events of pRostatic biopsY) study at the Urology section, Department of Surgery of the University of Catania (Local registration number: #131/2015). A total of 205 patients with elevated prostate-specific antigen (≥ 4 ng/ml) or clinical suspicion of PCa who underwent primary transperineal prostate biopsy were included in this cross-sectional study. The assessment of PIA, HGPIN, and PCa were performed by 2 experienced pathologists and samples were investigated for the presence of an inflammatory infiltrate, according to the Irani score. Primary and secondary Gleason grade of tumor in positive biopsies were evaluated according to the 2016 ISUP Modified Gleason System., Results: In the entire cohort, median age was 68.0 (interquartile range: 62.0-74.5), median prostate-specific antigen was 6.5 (interquartile range: 5.51-9.57). The prevalence of MetS was 34.1%, the detection rate of PCa was 32.7%, the rate of PIA was 28.3%, the rate of HGPIN was 32.2%, whereas the rate of severe intraprostatic inflammation (Irani-score ≥4) was 28.8%. When comparing clinical and histological variables in patients without and with PIA, metabolic aberrations where not significantly different in both groups. We did not find statistical association in detection rate of PCa (29.3% vs. 34.0%; P = 0.07) and HGPIN (27.6% vs. 34.0%; P = 0.37) in patients with and without PIA, respectively. When considering metabolic aberrations, MetS was not associated with Irani-score ≥4 (28.6% vs. 28.4%; P = 0.96) and none of each component was statistically predictive of severe inflammation. At the multivariable logistic regression analysis, PIA, HGPIN, and MetS were not associated with greater risk of PCa., Conclusion: In this study, we did not show an association between MetS and PIA and PCa. Although the small sample size and the cross-sectional nature of the study, we do not suppose that MetS could be associated with greater evidence of PIA. Further studies should be conducted to evaluate the exact nature of this pathological lesion., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Markers for prostate cancer (PCa) have progressed over recent years. In particular, the prostate health index (PHI) and the 4-kallikrein (4K) panel have been demonstrated to improve the diagnosis of PCa. We aimed to review the diagnostic accuracy of PHI and the 4K panel for PCa detection. We performed a systematic literature search of PubMed, EMBASE, Cochrane, and Academic One File databases until July 2016. We included diagnostic accuracy studies that used PHI or 4K panel for the diagnosis of PCa or high-grade PCa. The methodological quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. Twenty-eight studies including 16,762 patients have been included for the analysis. The pooled data showed a sensitivity of 0.89 and 0.74 for PHI and 4K panel, respectively, for PCa detection and a pooled specificity of 0.34 and 0.60 for PHI and 4K panel, respectively. The derived area under the curve (AUC) from the hierarchical summary receiver operating characteristic (HSROC) showed an accuracy of 0.76 and 0.72 for PHI and 4K panel respectively. For high-grade PCa detection, the pooled sensitivity was 0.93 and 0.87 for PHI and 4K panel, respectively, whereas the pooled specificity was 0.34 and 0.61 for PHI and 4K panel, respectively. The derived AUC from the HSROC showed an accuracy of 0.82 and 0.81 for PHI and 4K panel, respectively. Both PHI and the 4K panel provided good diagnostic accuracy in detecting overall and high-grade PCa., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Objective: To compare the prognostic accuracy of Prostate Health Index (PHI) and Prostate Cancer Antigen 3 in predicting pathologic features in a cohort of patients who underwent radical prostatectomy (RP) for prostate cancer (PCa)., Methods and Materials: We evaluated 156 patients with biopsy-proven, clinically localized PCa who underwent RP between January 2013 and December 2013 at 2 tertiary care institutions. Blood and urinary specimens were collected before initial prostate biopsy for [-2] pro-prostate-specific antigen (PSA), its derivates, and PCA3 measurements. Univariate and multivariate logistic regression analyses were carried out to determine the variables that were potentially predictive of tumor volume > 0.5 ml, pathologic Gleason sum ≥ 7, pathologically confirmed significant PCa, extracapsular extension, and seminal vesicles invasions., Results: On multivariate analyses and after bootstrapping with 1,000 resampled data, the inclusion of PHI significantly increased the accuracy of a baseline multivariate model, which included patient age, total PSA, free PSA, rate of positive cores, clinical stage, prostate volume, body mass index, and biopsy Gleason score (GS), in predicting the study outcomes. Particularly, to predict tumor volume > 0.5, the addition of PHI to the baseline model significantly increased predictive accuracy by 7.9% (area under the receiver operating characteristics curve [AUC] = 89.3 vs. 97.2, P>0.05), whereas PCA3 did not lead to a significant increase. Although both PHI and PCA3 significantly improved predictive accuracy to predict extracapsular extension compared with the baseline model, achieving independent predictor status (all P's < 0.01), only PHI led to a significant improvement in the prediction of seminal vesicles invasions (AUC = 92.2, P < 0.05 with a gain of 3.6%). In the subset of patients with GS ≤ 6, PHI significantly improved predictive accuracy by 7.6% compared with the baseline model (AUC = 89.7 vs. 97.3) to predict pathologically confirmed significant PCa and by 5.9% compared with the baseline model (AUC = 83.1 vs. 89.0) to predict pathologic GS ≥ 7. For these outcomes, PCA3 did not add incremental predictive value., Conclusions: In a cohort of patients who underwent RP, PHI is significantly better than PCA3 in the ability to predict the presence of both more aggressive and extended PCa., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Introduction: The aim of this study was to determine the prevalence of TIN and multifocality in men undergoing radical orchiectomy for testicular germ cell tumor (TGCT), and among those with a main tumor size ≤ 2 cm, potentially eligible for testis-sparing surgery., Patients and Methods: Orchiectomy specimens from 126 consecutive patients treated for TGCT tumor between 2003 and 2012 were included. Multifocality was defined as a distinct tumor focus with a diameter ≥ 1 mm separable from the main tumor mass. Uni- and multivariate logistic regression was performed to identify the association between pathological variables and multifocality and to identify variables for predicting clinical stage II to III and pathological stage ≥ pT2., Results: Of the 126 patients, 103 (82.0%) had clinical stage I cancer at presentation and 23 (18.0%) had clinical stage II to III. The median size of the primary tumor mass was 3.7 cm (range, 0.5-12 cm) in multifocality and 3.0 cm (range, 0.6-8.0 cm) in monofocality, respectively (P < .05). The prevalence of multifocality and TIN was lower in the presence of a smaller main tumor mass (≤ 1 cm) compared with tumors 1.1 to 2.0 cm (P < .05), and increased when the index mass tumor diameter was ≥ 2 cm (P trend < .05). No association was found between tumor histology and multifocality (P = .95) or TIN (P = .54) using the χ(2) test., Conclusion: The prevalence of multifocality and TIN was decreased in smaller tumors (≤ 1 cm) and increased when the index mass tumor diameter was ≥ 1.1 cm., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Objectives: To identify predictive factors of unfavorable disease and of biochemical failure in patients treated with radical prostatectomy but eligible for active surveillance (AS) according to Prostate Cancer Research International: Active Surveillance (PRIAS) criteria. We aimed to introduce and validate the percentage of cancer involvement in positive cores (CIPC) as potential worse predictive factor., Methods: From January 2002 to December 2007, 750 consecutive subjects underwent radical prostatectomy at a single institution. We identified 147 (19.05%) patients who were eligible for AS based on PRIAS criteria: clinical stage T1c or T2 disease, prostate-specific antigen level of ≤ 10 ng/ml, Gleason score ≤ 6, prostate-specific antigen-D of<0.2 ng/ml(2), and fewer than 3 positive biopsy cores. CIPC was included in the analysis., Results: Of the 147 patients, 95 (66.43%) patients had favorable disease, whereas 48 (33.57%) had unfavorable disease. In multivariate logistic regression, maximum cancer length (odds ratio 12.52, P<0.01) and CIPC (odds ratio 1.70, P<0.01) represented independent predictors of unfavorable prostate cancer. The area under the receiver operating characteristics curve analysis revealed significantly higher performance after including CIPC to the PRIAS criteria (0.61 vs. 0.94, P<0.01). A cutoff of 0.4mm of CIPC was set to predict unfavorable disease with 93% specificity, 76% sensibility, and 87% accuracy based on the receiver operating characteristics curve analysis. Finally, the 3- and 5-years biochemical recurrence (BCR)-free survival were significantly lower in subjects with CIPC ≥ 0.4mm, 88.4 % and 81.0% vs. 97.8% and 95.7%, respectively (P< 0.01)., Conclusions: Our findings suggest that the inclusion of CIPC to the prostate biopsy features could be helpful to avoid misclassification in patients eligible for AS according to the PRIAS criteria., (Copyright © 2014 Elsevier Inc. All rights reserved.)