Learning curve for robot-assisted nipple-sparing mastectomy: A single institution experience

Abstract

Background: Robot-assisted nipple sparing mastectomy (RANSM) is emerging because it offers hidden incisions and ergonomic movements. In this study, we report the learning curve and feasibility of RANSM.

Methods: A retrospective study was conducted among women who underwent RANSM with immediate breast reconstruction from July 2019 to June 2022. All RANSM procedures were performed by a single surgeon. We divided all the cases into two phases: the early phase (cases 1 to 21) and the late phase (cases 22 to 46). The total operation time, breast operation time, docking time, and console time were analyzed, and the cumulative sum (CUSUM) method was used to evaluate the effects of case experience accumulation on the time required for RANSM. Postoperative complications were analyzed according to their Clavien-Dindo grade.

Results: Overall, 42 women underwent 46 RANSM procedures. In the early and late phases, the mean console times were 78.1 min and 60.1 min (p = 0.011), respectively. In learning curve analysis, 21 RANSM procedures were required to reduce the breast operation time. Two cases of Clavien-Dindo grade III postoperative complications occurred (4.3 %). One case was an implant removal caused by infection, and the other was partial nipple ischemia; both occurred in the early phase, with none in the late phase.

Conclusions: The breast operation time improved after the 21st RANSM procedure, and only two cases had Clavien-Dindo grade III or higher postoperative complications. RANSM is thus technically feasible and acceptable, with a short learning curve.

Keywords: Breast cancer; Nipple-sparing mastectomy; Robotic surgery; Robotic-assisted nipple-sparing mastectomy.