Learning curves in minimally invasive hepatectomy: systematic review and meta-regression analysis

Abstract

BACKGROUND: Minimally invasive hepatectomy (MIH) has become an important option for the treatment of various liver tumours. A major concern is the learning curve required. The aim of this study was to perform a systematic review and summarize current literature analysing the learning curve for MIH. METHODS: A systematic review of the literature pertaining to learning curves in MIH to July 2019 was performed using PubMed and Scopus databases. All original full-text articles published in English relating to learning curves for both laparoscopic liver resection (LLR), robotic liver resection (RLR), or a combination of these, were included. To explore quantitatively the learning curve for MIH, a meta-regression analysis was performed. RESULTS: Forty studies relating to learning curves in MIH were included. The median overall number of procedures required in studies utilizing cumulative summative (CUSUM) methodology for LLR was 50 (range 25-58) and for RLR was 25 (16-50). After adjustment for year of adoption of MIH, the CUSUM-derived caseload to surmount the learning curve for RLR was 47.1 (95 per cent c.i. 1.2 to 71.6) per cent; P = 0.046) less than that required for LLR. A year-on-year reduction in the number of procedures needed for MIH was observed, commencing at 48.3 cases in 1995 and decreasing to 23.8 cases in 2015. CONCLUSION: The overall learning curve for MIH decreased steadily over time, and appeared less steep for RLR compared with LLR.