Affiliation:
1. Department of Gastroenterological Surgery The Cancer Institute Hospital of Japanese Foundation for Cancer Research Tokyo Japan
2. Department of Surgery Saiseikai Kumamoto Hospital Kumamoto Japan
3. Department of Gastroenterological Surgery, Graduate School of Medical Sciences Kumamoto University Kumamoto Japan
4. Department of Clinical Trial and Management The Cancer Institute Hospital of Japanese Foundation for Cancer Research Tokyo Japan
Abstract
AbstractBackgroundThough laparoscopic gastrectomy (LG) has become the gold standard for gastric cancer treatment according to the Japanese treatment guidelines, its learning curve remains steep. Decreasing numbers of surgeons and transitions in the work environment have changed LG training recently. We analyzed LG training over the last decade to identify factors affecting the learning curve.Study DesignLaparoscopic distal and pylorus‐preserving gastrectomies conducted between 2010 and 2020 were included. We assessed learning curves based on the standard operation time (SOT) defined by analysis of covariance. Then we divided the trainees into two groups based on the length of the learning curve and examined the factors affecting the learning curve with linear regression analysis.ResultsAmong 2335 LGs, 960 cases treated by 27 trainees and 1301 cases treated by six attending surgeons were analyzed. The operation time was prolonged (p = 0.009) and postoperative morbidity rates were lower (p = 0.0003) for cases treated by trainees. Trainees experienced 38 (range, 9–81) cases as scopists and nine (range, 0–41) cases as first assistants to the first operator. The learning curve was approximately 30 cases. The SOT was calculated based on gender, body mass index, tumor location, reconstruction, and lymph node dissection. Trainees who had shorter learning curves had more experience (51–100 cases) with any laparoscopic surgery before LG training than the others (11–50 cases, p = 0.017).ConclusionSufficient experience with laparoscopic surgery before starting LG training might contribute to the efficiency of LG training and shorten the learning curve.