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.