Effects of the learning curve on operative time and lymph node harvesting during robotic gastrectomy

Background: Gastric cancer is the fifth most frequent cancer globally. The introduction of minimally invasive surgery for gastric cancer aimed at reducing post-operative morbidity and hospital length of stay. Although the role of laparoscopic gastrectomy has been established, robotic gastric surgery has only recently gained popularity. The purpose of this study was to evaluate, with a multidimensional analysis, the learning curve of a single surgeon with extensive experience in laparoscopic gastrectomy. Methods: We prospectively collected data from 104 gastric cancer patients who underwent surgery with a robotic approach from June 2015 to June 2019 by a single surgeon. We performed 21 total gastrectomies (TGs) and 83 subtotal gastrectomies (STGs). A D2 lymphadenectomy was performed in all the patients. Proximal and distal resection margins were tumoour-free in all patients. There were no intraoperative complications, and no conversions occurred. Results: The plateau of the learning curve based on harvesting lymph nodes and operative time was not reached for TG. The learning curve of operative time for STG could be divided into three different phases: an early or learning phase from 1 to 27 cases, an intermediate or proficiency phase from 28 to 48 cases, and a late or mastery phase from 49 to 83 cases. The learning curve for harvesting lymph nodes was achieved after 41 cases in the STG group. Conclusion: This study shows that robotic gastrectomy is a complex procedure with a significant multiphasic learning curve. Nevertheless, the robotic learning curve seems to be more rapid than that of conventional laparoscopy. Most importantly, our results suggest that the robotic technique can provide oncological adequacy in terms of lymph node harvesting even in the very first phase of the learning curve.