No abstract

No abstract

The aim of this study was to develop nomograms for predicting prostate cancer and its zonal location using prostate-specific antigen density, prostate volume, and their zone-adjusted derivatives. A total of 928 consecutive patients with prostate-specific antigen (PSA) less than 20.0 ng/mL, who underwent transrectal ultrasound-guided transperineal 12-core prostate biopsy at West China Hospital between 2011 and 2014, were retrospectively enrolled. The patients were randomly split into training cohort (70%, n = 650) and validation cohort (30%, n = 278). Predicting models and the associated nomograms were built using the training cohort, while the validations of the models were conducted using the validation cohort. Univariate and multivariate logistic regression was performed. Then, new nomograms were generated based on multivariate regression coefficients. The discrimination power and calibration of these nomograms were validated using the area under the ROC curve (AUC) and the calibration curve. The potential clinical effects of these models were also tested using decision curve analysis. In total, 285 (30.7%) patients were diagnosed with prostate cancer. Among them, 131 (14.1%) and 269 (29.0%) had transition zone prostate cancer and peripheral zone prostate cancer. Each of zone-adjusted derivatives-based nomogram had an AUC more than 0.75. All nomograms had higher calibration and much better net benefit than the scenarios in predicting patients with or without different zones prostate cancer. Prostate-specific antigen density, prostate volume, and their zone-adjusted derivatives have important roles in detecting prostate cancer and its zonal location for patients with PSA 2.5-20.0 ng/mL. To the best of our knowledge, this is the first nomogram using these parameters to predict outcomes of 12-core prostate biopsy. These instruments can help clinicians to increase the accuracy of prostate cancer screening and to avoid unnecessary prostate biopsy.

No abstract

Background:The clinical value of perineural invasion (PNI) in patients with localized prostate cancer (PCa) is widely explored. However, its role in metastatic PCa (mPCa) remains unknown. Objectives: We aim to investigate the clinical significance of PNI in patients with mPCa. Materials and methods: Data of 515 mPCa patients between 2012 and 2018 were retrospectively studied. PNI and its intensity were identified by prostate biopsy. The prognostic value of PNI was evaluated by Kaplan-Meier curves and Cox proportional-hazards model. Results: Perineural invasion was detected in 170/515 (33.0%) cases. Among them 73/170 (42.9%) and 97/170 (57.1%) harbored unifocal PNI (uni-PNI) and multifocal PNI (multi-PNI), respectively. Compared to patients without PNI, those with PNI had statistically shorter castration-resistant PCa-free survival (CFS) and numerically shorter overall survival (OS) (mCFS: 15.4-vs. 18.5-Mo, p = 0.015; mOS: 63.8-vs. 71.4-Mo, p = 0.108). Patients harboring multi-PNI were associated with poorer clinical outcomes than those with uni-PNI (mCFS: 12.4-vs. 18.0-Mo, p = 0.040; mOS: 39.7-Mo vs. NR, p = 0.018) or those without PNI (mCFS: 12.4-vs. 18.5-Mo, p = 0.002; mOS: 39.7-vs. 71.4-Mo, p = 0.002). Totally, neither uni-PNI nor multi-PNI was an independent risk factor impacting survival outcomes in multivariate analyses. While remarkably, for patients with favorable/intermediate-risk mPCa, multi-PNI was an independent adverse prognosticator for both CFS and OS (CFS: HR: 1.705, 95% CI: 1.029-2.825, p = 0.038; OS: HR: 3.294, 95% CI: 1.464-7.413, p = 0.004). Discussion and Conclusion: This study filled the blank of the clinical significance of PNI in mPCa. We found that multi-PNI could distinguish men with relatively poor prognosis from patients initially regarded as with favorable survival outcomes by other prognosticators, and thus, avoid disease underestimation in this group of patients. Our finding would help physicians have a deeper understanding of the heterogeneity of mPCa and make better individualized therapeutic strategy.