Introduction
The perioperative advantages of robot-assisted laparoscopy have resulted
in its widespread adoption in the treatment of early stage cervical
cancer. Numerous observational studies and meta-analyses report superior
results in blood loss, hospital stay and complication rates compared
with the laparotomic approach.1-4 In addition, equal
survival rates of robot-assisted laparoscopy and laparotomy were
suggested.5-8 However, a recent trial by Ramirez et
al., which randomised between minimally invasive surgery (MIS) and
laparotomy, showed a significantly increased recurrence rate and reduced
overall survival in patients receiving MIS for FIGO stage IA1-IB1
cervical cancer.9 The MIS arm of this trial consisted
predominately of conventional laparoscopy with only 15.6% of the
patients operated by robot-assisted surgery. Multiple subsequent
observational studies have substantiated these results regarding MIS10-13, while others reported non-inferiority of
recurrence and survival rates after (specifically) robot-assisted
surgery.14-16
A large population-based cohort study in Sweden, where cervical cancer
surgery is highly centralised, recently concluded it to be safe to
continue with robot-assisted surgery when performed by experienced,
high-volume surgeons.14 In the previous studies, the
learning curve effect on oncological outcomes in cervical cancer –
specifically in robot-assisted laparoscopy – is not yet reported. This
could be a potential confounder and could offer a possible explanation
for the conflicting reports. In addition, until today the literature
available on learning curves has mainly focused on the duration of
surgery only.17-20 To analyse proficiency in
robot-assisted laparoscopy the oncological outcome should be considered
the foremost relevant parameter. In other oncological diseases, for
instance prostate cancer, it has been shown that oncological outcomes
are associated with the learning curve of robot-assisted surgery but the
amount of procedures needed to reach an accepted plateau of the learning
curve varies widely and requires further
research.21,22
The objective of this study is to investigate the learning curve of a
single surgical team and its effect on the risk of cervical cancer
recurrence and to quantify impact on survival. By using a multivariate
risk-adjusted cumulative sum analysis we aim to establish the number of
surgeries needed to ascertain – oncological – proficiency in
robot-assisted laparoscopy in the treatment of early stage cervical
cancer.