Learning curve for robot-assisted neck dissection in head and neck cancer: a 3-year prospective case study and analysis.

Abstract

Robot-assisted neck dissection (RAND) for the management of regional metastases is a recently developed technique in the field of head and neck cancer that uses a robotic surgical system. This is the first report that estimates the learning curve for RAND. To evaluate a learning curve for RAND according to the types of neck dissection and report clinical outcomes. Prospective case study of 90 patients undergoing neck dissection between May 2010 and April 2013 at a university tertiary referral center. Fifty modified radical neck dissections (MRNDs) and 40 supraomohyoid neck dissections (SONDs) were performed by a single surgeon using a robotic surgical system to treat head and neck cancer. The MRND and the SOND groups were subdivided into 5 and 4 consecutive subgroups of 10 patients each, respectively. Perioperative parameters were compared, including mean operation time, duration and amount of drainage, length of hospital stay, and postoperative complications. Significant decreases in mean operation time were observed as experience performing RAND increased in both the MRND and the SOND groups. The mean operation time for the MRND group decreased by 29% over the course of our study (initial subgroup, 298.1 minutes; last subgroup, 212.4 minutes). The mean operation time for the SOND group decreased by 53% over the course of our study (initial subgroup, 226.5 minutes; last subgroup, 106.1 minutes). There were no significant differences between subgroups for the other perioperative parameters. We explored the RAND learning curve in a single institution over a 3-year period. This study can be used as a timeline reference for institutions where the RAND procedure will be adopted as an alternative procedure.