Development and validation of a novel comorbidity score specific for prostate cancer patients treated with robotic platform and its implication on DaVinci single-port system.

To develop and validate a novel Comorbidity score for Robotic Surgery (CRS) in predicting severe complications after robot-assisted radical prostatectomy (RARP). Furthermore, we investigated the impact of the surgical platform (Multi-Port - MP vs Single-Port - SP) according to this score. We included 2085 ("development cohort") and 595 ("validation cohort") patients undergoing RARP at two tertiary referral centers between 2014 and March 2024 in a retrospective study. Statistical analyses included validation of the Charlson Comorbidity Index (CCI) to predict 30-day severe complications (Clavien-Dindo ≥ 3a), development and external validation of CRS using calibration plots and decision curve analysis. Lastly, locally weighted scatterplot smoothing (LOWESS) analysis was used to graphically explore the impact of the robotic platform according to novel CRS. CCI exhibited limited predictive ability for severe complications (60% in the validation cohort). In multivariable logistic regression analyses testing the correlation between each condition included in CCI and severe complications, diabetes and myocardial infarction resulted as independent predictors (OR 1.75 [95%CI 1.05-2.82]; OR 1.92 [95%CI 1.26-2.88]) and were subsequently fitted into a multivariable logistic model including age, previous abdominal surgery and obesity (BMI > 30). The resulting predictive model demonstrated superior discrimination and clinical net benefit in predicting severe complications compared to CCI (AUC 64 vs 60%). At LOWESS analysis, SP platform was associated with lower risk of severe complications as CRS increased compared to MP system. The validated CRS showed better accuracy compared to CCI in predicting severe complications after RARP. Additionally, the use of SP robotic platform may reduce the risk of severe complications in highly comorbid patients according to CRS.