Learning curve for adoption of robot-assisted minimally invasive esophagectomy: a systematic review of oncological, clinical, and efficiency outcomes


 Background: Robot-assisted minimally invasive esophagectomy (RAMIE) is gaining increasing popularity as an operative approach. Learning curves to achieve surgical competency in robotic-assisted techniques have shown significant variation in learning curve lengths and outcomes. This study aimed to summarize the current literature on learning curves for RAMIE. Methods: A systematic review was conducted in line with PRISMA guidelines. Electronic databases PubMed, MEDLINE, and Cochrane Library were searched, and articles reporting on learning curves in RAMIE were identified and scrutinized. Studies were eligible if they reported changes in operative outcomes over time, or learning curves, for surgeons newly adopting RAMIE. Results: Fifteen studies reporting on 1767 patients were included. Nine studies reported on surgeons with prior experience of robot-assisted surgery prior to adopting RAMIE, with only four studies outlining a specified RAMIE adoption pathway. Learning curves were most commonly analyzed using cumulative sum control chart (CUSUM) and were typically reported for lymph node yields and operative times, with significant variation in learning curve lengths (18–73 cases and 20–80 cases, respectively). Most studies reported adoption without significant impact on clinical outcomes such as anastomotic leak; significant learning curves were more likely in studies, which did not report a formal learning or adoption pathway. Conclusion: Reported RAMIE adoption phases are variable, with some authors suggesting significant impact to patients. With robust training through formal programmes or proctorship, however, others report RAMIE adoption without impact on clinical outcomes. A formalized adoption curriculum appears critical to prevent adverse effects on operative efficiency and patient care.