Authors
Ilse G.T. Baetena, Jacob P. Hoogendama, Henk W.R. Schreudera, Ina M. Jürgenliemk-Schulzb, Cornelis G. Geresteina, Ronald P. Zweemera
a Department of Gynaecological Oncology, Division of Imaging and Oncology, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
b Department of Radiology and Nuclear Medicine, Division of Imaging and Oncology, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
Corresponding author: Ilse G.T. Baeten, MD, Department of Gynaecological Oncology, Division of Imaging and Oncology, University Medical Center Utrecht, PO Box 85500, Utrecht 3508 GA, The Netherlands. Email: i.g.t.baeten@umcutrecht.nl
Running title: Learning curve of robot-assisted gynaecological surgery

Abstract

Objective Effect on patient outcomes when introducing a novice robotic surgeon, trained in accordance with a structured learning curriculum, to an experienced robotic surgery team.
Design Observational cohort study.
Setting Tertiary referral centre.
Population Patients with early-stage cervical cancer who were treated with primary robot-assisted surgery between 2007 and 2019. In addition to the 165 patients included in a former analysis, we included a further 61 consecutively treated patients and divided all patients over three groups: early learning phase of 61 procedures (group 1), experienced phase of the 104 procedures thereafter (group 2), and the final 61 procedures during introduction of a novice with structured training (group 3).
Methods Risk-adjusted cumulative sum (RA-CUSUM) analysis was performed and patient outcomes between groups were compared.
Main Outcome Measures Surgical proficiency based on recurrence, surgical and oncological outcomes.Results Based on RA-CUSUM analysis, no learning curve effect was observed for group 3. Regarding surgical outcomes, mean operation time in group 3 was significantly shorter than group 1 (p <0.001) and similar to group 2 (p =0.96). Proportions of intraoperative and postoperative adverse events in group 3 were not significantly different from the experienced group (group 2). Regarding oncological outcomes, the 5-year disease-free survival, disease-specific survival, and overall survival in group 3 were not significantly different from the experienced group.
Conclusions Introducing a novice robotic surgeon, who was trained in accordance with a structured learning curriculum, resulted in similar patient outcomes as by experienced surgeons suggesting novices can progress through a learning phase without compromising outcomes of cervical cancer patients.
Keywords Cervical cancer; robot-assisted surgery; learning curve; cumulative sum analysis

Introduction

Learning curve effects seem unavoidable when adopting new and complex surgical technologies.1, 2 This appeared to be no different when robot-assisted surgery was adopted for gynaecological oncology two decades ago.3 Since then, several studies in the gynaecological oncology field reported on short-term surgical outcomes of robot-assisted surgery during the learning curve, e.g. operation time or blood loss. Until recently, learning curve effect on long-term outcomes, such as survival, were often omitted.4-7 Multiple studies on robot-assisted surgery for cervical cancer showed worse survival outcomes in early stages of the learning curve versus after mastery.8-12 This learning curve effect could be one of the explanations for the results of recent retrospective and prospective studies reporting inferior survival of cervical cancer patients treated with minimally invasive surgery compared to open surgery.13, 14 These results underscored the need for structured and validated learning curricula intended to improve quality of care when introducing surgeons to a new technology, while minimizing learning curve effects and patient harm.15
Since the adoption of the surgical robot by gynaecologists, the learning environment has evolved. Training modalities like virtual reality simulation, cadaver training, proctoring and use of dual consoles emerged and showed to be effective in acquiring robotic skills.16-20 In the past years, these training modalities have been brought together into several structured learning curricula for robot-assisted gynaecological surgery, such as the Society of European Robotic Gynaecological Surgery (SERGS) curriculum.21 A prospectively validated curriculum is, however, still lacking.22 While training modalities keep evolving and qualitative research shows that fellows experience increased confidence when having access to these modalities, little is known about how existing curricula are performing in terms of actual skill acquisition, and how the acquired robotic skills translate into patient outcomes.22, 23
The aim of our study was to assess the learning curve of robot-assisted surgery for early-stage cervical cancer when introducing a novice robotic surgeon to an experienced surgical team and assess the effect on patient outcomes. Previously, we demonstrated a single-institutional learning curve required at least 61 procedures before levelling out when initially starting with robot-assisted surgery.8 By expanding our cohort with 61 consecutively treated cases during introduction of a novice, who was trained in accordance with a structured learning curriculum, we evaluated whether the learning curve of this novice surgeon impacted surgical and oncological outcomes of early-stage cervical cancer patients.

Methods