Learning curve of laparoscopic and robotic total gastrectomy: a systematic review and meta-analysis

Abstract

Purpose: Minimally-invasive total gastrectomy (MITG) is associated with lower morbidity in comparison to open total gastrectomy but requires a learning curve (LC). We aimed to perform a pooled analysis of the number of cases required to surmount the LC (NLC) in MITG. Methods: A systematic review of PubMed, Embase, Scopus and the Cochrane Library from inception until August 2022 was performed for studies reporting the LC in laparoscopic total gastrectomy (LTG) and/or robotic total gastrectomy (RTG). Poisson mean (95% confidence interval [CI]) was used to determine the NLC. Negative binomial regression was performed as a comparative analysis. Results: There were 12 articles with 18 data sets: 12 data sets (n = 1202 patients) on LTG and 6 data sets (n = 318 patients) on RTG. The majority of studies were conducted in East Asia (94.4%). The majority of the data sets (n = 12/18, 66.7%) used non-arbitrary analyses. The NLC was significantly smaller in RTG in comparison to LTG [RTG 20.5 (95% CI 17.0–24.5); LTG 43.9 (95% CI 40.2–47.8); incidence rate ratio 0.47, p < 0.001]. The NLC was comparable between totally-laparoscopic total gastrectomy (TLTG) and laparoscopic-assisted total gastrectomy (LATG) [LATG 39.0 (95% CI 30.8–48.7); TLTG 36.0 (95% CI 30.4–42.4)]. Conclusions: The LC for RTG was significantly shorter for LTG. However existing studies are heterogeneous.