The prediction of post-prostatectomy incontinence (PPI) after robot-assisted radical prostatectomy (RARP) depends on multiple clinical, anatomical and surgical factors. There are only few risk formulas, tables or nomograms predicting PPI that may assist clinicians and their patients in adequate risk counseling on postoperative side-effects. Prospective data collection of 1814 patients who underwent RARP between 2009 and 2017 was done. Pre-operative parameters were age, body mass index (BMI), prostate volume, the American Society of Anesthesiologists (ASA) score, severity of Lower Urinary Tract Symptoms (LUTS), type of planned nerve-sparing surgery and surgical experience. The continence status was reported using Patient Reported Outcome Measurements (PROMs) using the validated pad-use questionnaire EPIC26. Continence was defined as either the use of zero pads or one safety pad. Multivariable logistic regression analysis was performed to identify predictors of PPI within one year after RARP. An online prediction tool was developed and validated. The median follow-up was 36 months (range 12-108). The response rate was high at 85.2%. A total of 85% (1537/1814) of patients was continent on follow-up. One-year continence rate was 80.1% (95% CI 78.3-81.9%) (1453/1814) and increased to 87.4% (95% CI 85.4-89.4%) after 5 years. On multivariable analysis, severity of LUTS (OR = 0.56 p = 0.004), higher age (OR = 0.73 p = 0.049), extend of nerve-sparing surgery (OR = 0.60 p = 0.001) and surgeon experience (OR = 1.48 p = 0.025) were significant independent predictors for PPI. The online prediction model performed well in predicting continence status with poor discrimination and good calibration. An intuitive online tool was developed to predict PPI after RARP that may assist clinicians and their patients in counseling of treatment.
Journal of robotic surgery. 2020 Sep 15 [Epub ahead of print]
Eelco R P Collette, Sjoerd O Klaver, Birgit I Lissenberg-Witte, Dies van den Ouden, Reindert J A van Moorselaar, André N Vis
Department of Urology, Maasstad Hospital, Rotterdam, The Netherlands. ., Department of Urology, Maasstad Hospital, Rotterdam, The Netherlands., Department of Epidemiology and Data Science, Amsterdam UMC, VU University Medical Center, Amsterdam, The Netherlands., Department of Urology, Amsterdam UMC, VU University Medical Center, room 4F27, De Boelelaan 1117, Postbus 7057, Amsterdam, 1081HV, The Netherlands.