Search

The study aimed to test if Briganti’s 2012 nomogram could be associated with the risk of prostate cancer (PCa) progression in European Association of Urology (EAU) intermediate-risk patients treated with robotic surgery. From January 2013 to December 2021, 527 consecutive patients belonging to the EAU intermediate-risk class were selected. Briganti’s 2012 nomogram, which predicts the risk of pelvic lymph node invasion (PLNI), was assessed as a continuous and dichotomous variable that categorized up to the median of 3.0%. Disease progression defined as biochemical recurrence and/or metastatic progression was evaluated by Cox proportional hazards (univariate and multivariate analysis). After a median follow-up of 95.0 months (95% confidence interval [CI]: 78.5–111.4), PCa progression occurred in 108 (20.5%) patients who were more likely to present with an unfavorable nomogram risk score, independently by the occurrence of unfavorable pathology including tumor upgrading and upstaging as well as PLNI. Accordingly, as Briganti’s 2012 risk score increased, patients were more likely to experience disease progression (hazard ratio [HR] = 1.060; 95% CI: 1.021–1.100; P = 0.002); moreover, it also remained significant when dichotomized above a risk score of 3.0% (HR = 2.052; 95% CI: 1.298–3.243; P < 0.0001) after adjustment for clinical factors. In the studied risk population, PCa progression was independently predicted by Briganti’s 2012 nomogram. Specifically, we found that patients were more likely to experience disease progression as their risk score increased. Because of the significant association between risk score and tumor behavior, the nomogram can further stratify intermediate-risk PCa patients, who represent a heterogeneous risk category for which different treatment paradigms exist.

ABSTRACT Purpose We assessed the prognostic impact of the 2012 Briganti nomogram on prostate cancer (PCa) progression in intermediate-risk (IR) patients presenting with PSA

Background and objective: The Hugo RAS and DaVinci Xi systems are used for performing robot-assisted radical prostatectomy (RARP). This study aims to compare these two platforms providing granular and comprehensive data on their intraoperative performance. Methods: The Comparison of Outcomes of Multiple Platforms for Assisted Robotic surgery—Prostate (COMPAR-P) trial is a prospective post-market study (clinicaltrials.org NCT05766163). Enrollment began in March 2023, allocating patients to DaVinci or Hugo RAS for RARP, without selection criteria, for up to 50 consecutive cases. Two experienced console surgeons performed the procedures, following the same technique. Evaluation focused on timing, learning curves, malfunctioning events, complications, and users’ satisfaction, using standard statistical methods, including the cumulative summation analysis (CUSUM) for the learning curve assessment. Key findings and limitations: Fifty patients each were enrolled for DaVinci (DV-RARP) and Hugo RAS (H-RARP) RARP. Baseline features were balanced. DV-RARP showed significantly shorter “setup” and “console” phase durations than H-RARP (37 vs 55 min and 97 vs 126 min, respectively, p

Abstract The study aimed to evaluate the impact of abdominal drain placement (vs. omission) on perioperative outcomes of robot-assisted partial nephrectomy (RAPN), focusing on complications, time to canalization, deambulation, and pain management. A prospectively-maintained institutional database was queried to get data of patients who underwent RAPN for renal masses between January 2018 and May 2023 at our Institution. Baseline, surgical, and postoperative data were collected. Retrieved patients were stratified based upon placement of abdominal drain (Y/N). Descriptive analyses comparing the two groups were conducted as appropriate. After adjusting for potential confounders, a logistic regression analysis was conducted to evaluate significant predictors of any grade and “major” complications. 342 patients were included: 192 patients in the “drain group” versus 150 patients in the “no-drain” group. Renal masses were larger (p

Background: Treatment outcomes in intermediate-risk prostate cancer (PCa) may be impaired by adverse pathology misclassification including tumor upgrading and upstaging. Clinical predictors of disease progression need to be improved in this category of patients. Objectives: To identify PCa prognostic factors to define prognostic groups in intermediate-risk patients treated with robot-assisted radical prostatectomy (RARP). Design: Data from 1143 patients undergoing RARP from January 2013 to October 2020 were collected: 901 subjects had available follow-up, of whom 479 were at intermediate risk. Methods: PCa progression was defined as biochemical recurrence and/or local recurrence and/or distant metastases. Study endpoints were evaluated by statistical methods including Cox’s proportional hazards, Kaplan–Meyer survival curves, and binomial and multinomial logistic regression models. Results: After a median (interquartile range) of 35 months (15–57 months), 84 patients (17.5%) had disease progression, which was independently predicted by the percentage of biopsy-positive cores ⩾ 50% and the International Society of Urological Pathology (ISUP) grade group 3 for clinical factors and by ISUP > 2, positive surgical margins and pelvic lymph node invasion for pathological features. Patients were classified into clinical and pathological groups as favorable, unfavorable (one prognostic factor), and adverse (more than one prognostic factor). The risk of PCa progression increased with worsening prognosis through groups. A significant positive association was found between the two groups; consequently, as clinical prognosis worsened, the risk of detecting unfavorable and adverse pathological prognostic clusters increased in both unadjusted and adjusted models. Conclusion: The study identified factors predicting disease progression that allowed the computation of highly correlated prognostic groups. As the prognosis worsened, the risk of PCa progression increased. Intermediate-risk PCa needs more prognostic stratification for appropriate management.