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.
Humans ; Male ; Prostatic Neoplasms/surgery* ; Nomograms ; Disease Progression ; Robotic Surgical Procedures ; Aged ; Middle Aged ; Prostatectomy/methods* ; Lymphatic Metastasis/pathology* ; Risk Assessment/methods* ; Proportional Hazards Models ; Retrospective Studies