Determining the Learning Curve for Robot-Assisted Simple Prostatectomy in Surgeons Familiar with Robotic Surgery

Purpose: Robot-assisted simple prostatectomy (RASP) has excellent outcomes when treating large volume prostates and incorporates the already familiar skills to most robotic surgeons. Our objective was to determine the learning curve for RASP. Materials and Methods: A retrospective review of RASP on 120 consecutive cases performed by two experienced robotic surgeons from 2014 to 2017 was conducted. We defined learning curve as the point at which operative parameters transition from logarithmic to linear improvement. Scatter plots of operative outcomes were constructed and logarithmic and linear best-fit line were estimated to determine the point of transition from logarithmic to linear improvement. Results: Surgeon 1 operated on 76 cases and surgeon 2 on 44 cases. The median age of the 120 patients who underwent RASP was 70.0 years (interquartile range [IQR] 65.0-74.0 years) and median prostate mass was 121.5g (IQR=102.0-149.3). Overall, high-grade complication rate was 7.5%; median hematocrit change was 5.4% (IQR=3.2-7.7) and tissue yield was 61.2g (IQR=49.7-76.9). Tissue yield demonstrated logarithmic improvement over the first 12 cases and then transitioned to a linear patter for one surgeon. Operative time in the last 10 cases was statistically different from the first 10 cases (p<0.01). Drop in hematocrit (Hct) for surgeon 2 demonstrated logarithmic improvement for the first 10 cases and then transitioned to a linear pattern. Conclusion: The learning curve for RASP varied depending on the variable examined. Blood loss (Hct) and tissue yield showed the greatest improvement over time, but neither showed significant improvement beyond 12 cases. We estimated the learning curve for RASP to be approximate to 10 to 12 cases for experienced robotic surgeons.