, Volume 28, Issue 6, pp 815-821
Date: 15 Dec 2012

Learning curve for robotic-assisted laparoscopic rectal cancer surgery

Rent the article at a discount

Rent now

* Final gross prices may vary according to local VAT.

Get Access



One of the main uses of robotic assisted abdominal surgery is the mesorectal excision in patients with rectal cancer. The aim of the present study is to analyse the learning curve for robotic assisted laparoscopic resection of rectal cancer.

Patients and methods

We included in our study 43 consecutive rectal cancer resections (16 females and 27 males) performed from January 2008 through December 2010. Mean age of patients was 66 ± 9.0 years. Surgical procedures included both abdomino-perineal and anterior resections. We analysed the following parameters: demographic data of the patients included in the study, intra- and postoperative data, time taking to set up the robot for operations (set-up or docking time), operative time, intra- and postoperative complications, conversion rates and pathological specimen features. The learning curve was analysed using cumulative sum (CUSUM) methodology.


The procedures understudied included seven abdomino-perineal resections and 36 anterior resections. In our series of patients, mean robotic set-up time was 62.9 ± 24.6 min, and the mean operative time was 197.4 ± 44.3 min. Once we applied CUSUM methodology, we obtained two graphs for CUSUM values (operating time and success), both of them showing three well-differentiated phases: phase 1 (the initial 9–11 cases), phase 2 (the middle 12 cases) and phase 3 (the remaining 20–22 cases). Phase 1 represents initial learning; phase 2 plateau represents increased competence in the use of the robotic system, and finally, phase 3 represents the period of highest skill or mastery with a reduction in docking time (p = 0.000), but a slight increase in operative time (p = 0.007).


The CUSUM curve shows three phases in the learning and use of robotic assisted rectal cancer surgery which correspond to the phases of initial learning of the technique, consolidation and higher expertise or mastery. The data obtained suggest that the estimated learning curve for robotic assisted rectal cancer surgery is achieved after 21–23 cases.