A systematic review of the learning curve in robotic surgery: range and heterogeneity

Background: With the rapid adoption of the robotic surgery, more and more learning curve (LC) papers are being published but there is no set definition of what should constitute a rigorous analysis and represent a true LC. A systematic review of the robotic surgical literature was undertaken to determine the range and heterogeneity of parameters reported in studies assessing the LC in robotic surgery.

Methods: The search was conducted in July 2017 in PubMed. All studies reporting a LC in robotic surgery were included. 268 (25%) of the identified studies met the inclusion criteria.

Results: 102 (38%) studies did not define nor explicitly state the LC with appropriate evidence; 166 studies were considered for quantitative analysis. 46 different parameters of 6 different outcome domains were reported with a median of two parameters (1-8) and 1 domain (1-5) per study. Overall, three domains were only technical and three domains were both technical and clinical/patient-centered outcomes. The two most commonly reported domains were operative time [146 studies (88%)] and intraoperative outcomes [31 studies (19%)]. Postoperative outcomes [16 studies (9%)] and surgical success [11 studies (7%)] were reported infrequently. Purely technical outcomes were the most frequently used to assess LC [131 studies (79%)].

Conclusions: The outcomes reported in studies assessing LC in robotic surgery are extremely heterogeneous and are most often technical indicators of surgical performance rather than clinical and patient-centered outcomes. There is no single outcome that best represents the surgical success. A standardized multi-outcome approach to assessing LC is recommended.