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.