Robotic Radical Prostatectomy Learning Curve of a Fellowship-Trained Laparoscopic Surgeon

Abstract

Background and Purpose: Several experienced practitioners of open surgery with limited or no laparoscopic background have adopted robot-assisted laparoscopic radical prostatectomy (RLRP) as an alternative to open radical prostatectomy (RRP), demonstrating outcomes comparable to those in large RRP and laparoscopic prostatectomy series. Thus, the significance of prior laparoscopic skills seems unclear. The learning curve, with respect to operative time and complications, in the hands of a devoted laparoscopic surgeon has not been critically assessed. We evaluated the learning curve of a highly experienced laparoscopic surgeon in achieving expertise with RLRP. Patients and Methods: We prospectively evaluated 150 consecutive patients undergoing RLRP by a single surgeon between March 2003 and September 2005. The first 25 cases were performed with the assistance of a surgeon experienced in open RRP. Data were compared for the first, second, and third groups of 50 cases. Demographic data were similar for the three groups. Urinary and sexual function data were evaluated subjectively and objectively using the RAND-36v2 Survey and the UCLA PCI preoperatively and at 3, 6, and 12 months postoperatively. Results: The mean operative time, blood loss, and conversion rate decreased significantly with increasing experience. All open conversions occurred during the first 25 cases. Intraoperative and postoperative complication rates were similar among groups. Although the differences were not significant, urinary and sexual function recovery improved with experience. Conclusion: The RLRP learning curve for a fellowship-trained laparoscopic surgeon seems to be similar to that of laparoscopically naive yet experienced practitioners of open RRP. The RLRP is safe and reproducible and even during the learning curve can produce results similar to those reported in large RRP series. The importance of assistance by an experienced open RRP surgeon during the learning curve cannot be overemphasized.