Learning Curve of Robotic Rectal Surgery With Lateral Lymph Node Dissection: Cumulative Sum and Multiple Regression Analyses

Abstract

Objective: This study aimed to assess the learning curve of robotic rectal surgery, a procedure that has gained increasing focus in recent years because it is expected that the advanced devices used in this approach provide advantages resulting in a shorter learning curve than that of laparoscopic surgery. However, no studies have assessed the learning curve of robotic rectal surgery, especially when lateral lymph node dissection is required.

Design: This was a nonrandomized, retrospective study from a single institution.

Setting: All consecutive patients who underwent robotic rectal or sigmoid colon surgery by a single surgeon between February 2012 and July 2016 in the University of Tokyo Hospital were enrolled. The learning curve for console time was assessed using a cumulative sum analysis and multiple linear regression analysis.

Participants: A total of 131 consecutive patients underwent robotic rectal or sigmoid colon surgery performed by a single experienced surgeon. Of these, 41 patients received lateral lymph node dissection.

Results: A cumulative sum plot for console time demonstrated that the learning period could be divided into 3 phases: Phase I, Cases 1 to 19; Phase II, Cases 20 to 78; and Phase III, Cases 79 to 131. Multiple linear regression analysis indicated that console time decreased significantly from one phase to another (Phase I-II, Δconsole time 83.0 minutes; Phase II-III, Δconsole time 40.1 minutes). Other factors affecting console time included body mass index, operative procedure, and lateral lymph node dissection, but not neoadjuvant therapy (such as chemoradiotherapy) or depth of invasion. Lateral lymph node dissection required an additional 138.4 minutes.

Conclusions: Our findings suggest that the first phase of the learning curve consists of the first 19 cases, which seems sufficient to master the manipulation of robotic arms and to understand spatial relationships unique to the robotic procedure.

Keywords: Medical Knowledge; Patient Care; Practice-Based Learning and Improvement; cumulative sum; multiple regression analysis; rectal surgery; robotic surgery.