Strengths and Limitations
Since we started with robot-assisted surgery at our institution at the end of 2007 it was the standard of care for early stage cervical cancer, thus minimizing the risk of selection bias in our analysis. Another strength is that, in contrast to other studies on this subject, we performed a formal CUSUM analysis, which is considered the reference standard for studying surgical learning curves and recently emerged in other surgical fields.30,31 Also, given the objective outcome parameters (i.e. mortality), misclassification of the outcome status (i.e. information bias) is unlikely to have occurred.
There were several limitations to this study. First, the shorter follow-up time of the second group, inherent to the more recent surgery date in this group, could have led to overestimation of the learning curve effect. This effect is likely to be limited as the majority of the recurrences occurred in the first three years of follow-up, which 80.8% of the patients in group 2 completed (not significantly different from the first group). Also, survival analysis with Kaplan Meier plots corrects for differences in individual follow-up through censoring thus still providing reliable data. Secondly, other robot-assisted procedures were also performed in the period from December 2007 to April 2017 for high grade and serous endometrial cancer, which reinforces our finding that one needs at least 61 procedures before reaching surgical proficiency. The variety of robot-assisted procedures is an inescapable reality in the daily practice of a high-volume oncological centre and represents a practice comparable to other tertiary referral centres. This also applies to the diversity in the surgical treatments given to these relatively young patients with cervical cancer. Preservation of fertility is often desired and, if possible, radical surgery is performed without removal of the uterus. We chose to include all primary radical robot-assisted laparoscopies in early stage cervical cancer since the robot-assisted actions require equal surgical proficiency. Inevitably, individual learning curves may differ, but we did not do a per surgeon analysis. In any case, for daily practice institutional performance is more important than individual performance. In the end, teams will consist of both experienced and less experienced surgeons which should guarantee maintenance of team proficiency at an optimal level. Lastly, our analysis may have been affected by residual confounding, resulting from several factors contributing to the risk of recurrence, such as age, FIGO stage, parametrial involvement and lymph node status, all related to DFS.27 By using RA-CUSUM analysis we adjusted for these risk differences between patients but the limited number of events in some variables restricted the comprehensiveness of our model.