RESUMO
To evaluate the prognostic potential of the 2012 Briganti nomogram for pelvic lymph node invasion on disease progression after surgery in intermediate-risk (IR) prostate cancer (PCa) patients with favorable tumor grade (International Society of Urological Pathology grade group 1 or 2), eventually associated with adverse clinical features as PSA between 10 and 20 ng/mL and/or clinical stage T2b. All IR PCa patients treated with robot-assisted radical prostatectomy and eventually extended pelvic lymph node dissection at the Department of Urology of the Integrated University Hospital of Verona between 2013 and 2021, with the abovementioned features, and available follow-up were considered. The 2012 Briganti nomogram score was assessed both as a continuous and dichotomous variable, where a mean risk score of 4% was used a threshold. The independent predictor status of the nomogram score on disease progression defined as the occurrence of biochemical recurrence and/or metastatic progression was evaluated using the Cox regression analysis. Overall, 348 patients were enrolled in the study. Median (interquartile range) follow-up was 98 (83.5-112.4) months. At multivariable Cox regression analysis, PCa progression, which occurred in 65 (18.7%) cases, was independently predicted only by the 2012 Briganti nomogram score evaluated as a continuous variable, among all considered clinical features (HR 1.16; 95%CI 1.08-1.24; p < 0.001). In addition, patients presenting with a nomogram score ≥ 4% were more likely to experience disease progression even after adjustment for clinical (HR 2.22, 95%CI 1.02-4.79; p = 0.043) and pathological (HR 1.80; 95%CI 1.06-3.05; p = 0.031) factors. In the examined patient population, the 2012 Briganti nomogram predicted PCa progression after surgery. Accordingly, as the risk score increased, patients were more likely to progress, independently by the occurrence of adverse pathology in the surgical specimen. The 2012 Briganti nomogram score categorized according to the mean value allowed to identify prognostic subgroups.