Background: While multiple Asian and a few Western retrospective series have demonstrated the feasibility and safety of robotic-assisted gastrectomy for gastric cancer, its reliability for thorough resection, especially for locoregional disease, has not yet been firmly established, and reported learning curves vary widely. To support wider implementation of robotic gastrectomy, we evaluated the learning curve for this approach, assessed its oncologic feasibility, and created a selection model predicting the likelihood of conversion to open surgery in a US patient population.
Patients and methods: We retrospectively reviewed data on all consecutive patients who underwent robotic gastrectomy at a high-volume institution between May 2012 and March 2019.
Results: Of the 220 patients with gastric cancer selected to undergo curative-intent robotic gastrectomy, surgery was completed using robotics in 159 (72.3%). The median number of removed lymph nodes was 28, and ≥ 15 lymph nodes were removed in 94% of procedures. Surgical time decreased steadily over the first 60-80 cases. Complications were generally minor: 7% of patients experienced complications of grade 3 or higher, with an anastomotic leak rate of 2% and mortality rate 0.9%. Factors predicting conversion to open surgery included neoadjuvant chemotherapy, BMI ≥ 31 kg/m2, and tumor size ≥ 6 cm.
Conclusions: These findings support the safety and oncologic feasibility of robotic gastrectomy for selected patients with gastric cancer. Proficiency can be achieved by 20 cases and mastery by 60-80 cases. Ideal candidates for this approach are patients with few comorbidities, BMI < 31 kg/m2, and tumors < 6 cm.