Background Seminal vesicle invasion (SVI) is considered to be one of most adverse prognostic findings in prostate cancer, affecting the biochemical progression-free survival and disease-specific survival. Multiparametric magnetic resonance imaging (mpMRI) has shown excellent specificity in diagnosis of SVI, but with poor sensitivity. The aim of this study is to create a model that includes the Prostate Imaging Reporting and Data System version 2 (PI-RADS v2) score to predict postoperative SVI in patients without SVI on preoperative mpMRI. Methods A total of 262 prostate cancer patients without SVI on preoperative mpMRI who underwent radical prostatectomy (RP) at our institution from January 2012 to July 2019 were enrolled retrospectively. The prostate-specific antigen levels in all patients were <10 ng/mL. Univariate and multivariate logistic regression analyses were used to assess factors associated with SVI, including the PI-RADS v2 score. A regression coefficient-based model was built for predicting SVI. The receiver operating characteristic curve was used to assess the performance of the model. Results SVI was reported on the RP specimens in 30 patients (11.5%). The univariate and multivariate analyses revealed that biopsy Gleason grade group (GGG) and the PI-RADS v2 score were significant independent predictors of SVI (all P<0.05). The area under the curve of the model was 0.746 (P<0.001). The PI-RADS v2 score <4 and Gleason grade <8 yielded only a 1.8% incidence of SVI with a high negative predictive value of 98.2% (95% CI, 93.0-99.6%). Conclusions The PI-RADS v2 score <4 in prostate cancer patients with prostate-specific antigen level <10 ng/mL is associated with a very low risk of SVI. A model based on biopsy Gleason grade and PI-RADS v2 score may help to predict SVI and serve as a tool for the urologists to make surgical plans.

/pdf/predictive-model-containing-pi-rads-v2-score-for-3741nhc9lj.pdf

Predictive model containing PI-RADS v2 score for postoperative seminal vesicle invasion among prostate cancer patients

To explore an optimized grade group (oGG) criterion from systematic biopsies (SB) and targeted biopsies (TB) and offer a better prediction of radical prostatectomy (RP) grade group (GG).

Optimized grade group for reporting prostate cancer grade in systematic and MRI‐targeted biopsies

Simple Summary This study reports a significant association of pelvic inflammation with prostate cancer (PCa) aggressiveness in a large cohort of men undergoing robot-assisted laparoscopic prostatectomy (RALP) for localized PCa. In addition, PCa patients with pelvic inflammation had elevated expression of inflammation-associated genes and cancer-driving pathways in their tumors. Increased systemic inflammation with activation of the IL6-STAT pathway was seen in prostate cancer patients with pelvic inflammation. The presence of pelvic inflammation in prostate cancer patients suggests aggressive disease with a potential to develop biochemical recurrence and metastasis. This study is highly relevant as it allows us to follow prostate cancer patients with pelvic inflammation for metastasis closely. It also suggests that inhibiting the STAT-IL6 pathway would benefit these patients. Abstract The impact of pelvic inflammation on prostate cancer (PCa) biology and aggressive phenotype has never been studied. Our study objective was to evaluate the role of pelvic inflammation on PCa aggressiveness and its association with clinical outcomes in patients following radical prostatectomy (RP). This study has been conducted on a retrospective single-institutional consecutive cohort of 2278 patients who underwent robot-assisted laparoscopic prostatectomy (RALP) between 01/2013 and 10/2019. Data from 2085 patients were analyzed to study the association between pelvic inflammation and adverse pathology (AP), defined as Gleason Grade Group (GGG) > 2 and ≥ pT3 stage, at resection. In a subset of 1997 patients, the association between pelvic inflammation and biochemical recurrence (BCR) was studied. Alteration in tumor transcriptome and inflammatory markers in patients with and without pelvic inflammation were studied using microarray analysis, immunohistochemistry, and culture supernatants derived from inflamed sites used in functional assays. Changes in blood inflammatory markers in the study cohort were analyzed by O-link. In univariate analyses, pelvic inflammation emerged as a significant predictor of AP. Multivariate cox proportional-hazards regression analyses showed that high pelvic inflammation with pT3 stage and positive surgical margins significantly affected the time to BCR (p ≤ 0.05). PCa patients with high inflammation had elevated levels of pro-inflammatory cytokines in their tissues and in blood. Genes involved in epithelial-to-mesenchymal transition (EMT) and DNA damage response were upregulated in patients with pelvic inflammation. Attenuation of STAT and IL-6 signaling decreased tumor driving properties of conditioned medium from inflamed sites. Pelvic inflammation exacerbates the progression of prostate cancer and drives an aggressive phenotype.

/pdf/association-between-incidental-pelvic-inflammation-and-w8syinq2.pdf

Association between Incidental Pelvic Inflammation and Aggressive Prostate Cancer

Introduction Presently, prostate biopsy (PBx) results report the highest Gleason Grade Group (GGG) as a single metric that gauges the overall clinical aggressiveness of cancer and dictates treatment. We hypothesized a PBx showing multiple cores of cancer with more volume cancer per core would represent more aggressive disease. We propose the Weighted Gleason Grade Group (WGGG), a novel scoring system that synthesizes all histopathologic data and cancer volume into a single numeric value representing the entire PBx, allowing for improved prediction of adverse pathology and risk of biochemical recurrence (BCR) following radical prostatectomy (RP). Methods We studied 171 men who underwent RP after standard PBx. The WGGG was calculated by summing each positive core using the formula: GGG + (GGG x %Ca/core). RP pathology was evaluated for extraprostatic extension (EPE), positive surgical margins (PSM), seminal vesicle invasion (SVI), and lymph node involvement (LNI), and patients were followed for BCR. We compared GGG vs. WGGG receiver operating characteristic curves for each outcome, and determined the predictive capability of GGG and WGGG to identify patients with BCR. Categorized WGGG groups were created based on risk of BCR using classification and regression tree analysis. We then sought to externally validate WGGG in a cohort of 389 patients in a separate institutional dataset. Results In the development cohort, area under the curves (AUCs) for the WGGG vs. GGG were significantly higher for predicting EPE (0.784 vs. 0.690, P = 0.002), SVI (AUC 0.823 vs. 0.721, P = .014), LNI (AUC 0.862 vs. 0.823, P = 0.039), and PSM (AUC 0.638 vs. 0.575, P = 0.031. Analysis of the validation cohort showed similar findings for EPE (AUC 0.764 vs. 0.729, P = 0.13), SVI (AUC 0.819 vs. 0.749, P = 0.01), LNI (AUC 0.939 vs. 0.867, P = 0.02), and PSM (AUC 0.624 vs. 0.547, P = 0.04). Patients with WGGG >30 (high-risk group) demonstrated ∼50% failure at 2 years in both cohorts. Conclusions The WGGG, by providing a metric reflecting the entirety of the PBx, is more informative than conventional single GGG alone in identifying adverse pathologic outcomes and risk of BCR following RP. This superior discriminatory capability has been achieved without any consideration of other commonly available clinical disease characteristics.

Weighted Gleason Grade Group (WGGG): A new prostate cancer biopsy reporting system with prognostic potential.

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Weighted Gleason Grade Group (WGGG): A new prostate cancer biopsy reporting system with prognostic potential.