Real-time assessment of learning curve for robot-assisted laparoscopic prostatectomy

Abstract

Introduction The learning curves analysed to date for robot-assisted laparoscopic prostatectomy are based on arbitrary cut-offs of the total cases. Methods We analysed a large dataset of robot-assisted laparoscopic prostatectomies from a single centre between 2008 and 2019 for assessment of the learning curve for perioperative outcomes with respect to time and individual cases. Results A total of 1,406 patients were evaluated, with mean operative time 198.08 minutes and mean console time 161.05 minutes. A plot of operative time and console time showed an initial decline followed by a near-constant phase. The inflection points were detected at 1,398 days (308th case) for operative time and 1,470 days (324th case) for console time, with a declining trend of 8.83 minutes and 7.07 minutes, respectively, per quarter-year (p<0.001). Mean estimated blood loss showed a 70.04% reduction between the start (214.76ml) and end (64.35ml) (p<0.001). The complication rate did not vary with respect to time (p=0.188) or the number of procedures (p=0.354). There was insufficient evidence to claim that the number of operations (p=0.326), D’Amico classification (p=0.114 for intermediate versus low; p=0.158 for high versus low) or time (p=0.114) was associated with the odds of positive surgical margins. Conclusions It takes about 300 cases and nearly 4 years to standardise operative and console times, with a requirement of around 80 cases per annum for a single surgical team in the initial years to optimise the outcomes of robot-assisted laparoscopic prostatectomy.