Defining the learning curve of robotic thoracic surgery: what does it take?

Abstract

Background: Controversy exists as to what constitutes a learning curve to achieve competency, and how the initial learning period of robotic thoracic surgery should be approached.

Methods: We conducted a systematic review of the literature published prior to December 2018 using PubMed/MEDLINE for studies of surgeons adopting the robotic approach for anatomic lung resection or thymectomy. Changes in operating room time and outcomes based on number of cases performed, type of procedure, and existing proficiency with video-assisted thoracoscopic surgery (VATS) were examined.

Results: Twelve observational studies were analyzed, including nine studies on robotic lung resection and three studies on thymectomy. All studies showed a reduction in operative time with an increasing number of cases performed. A steep learning curve was described for thymectomy, with a decrease in operating room time in the first 15 cases and a plateau after 15-20 cases. For anatomic lung resection, the number of cases to achieve a plateau in operative time ranged between 15-20 cases and 40-60 cases. All but two studies had at least some VATS experience. Six studies reported on experience of over one hundred cases and showed continued gradual improvements in operating room time.

Conclusion: The learning curve for robotic thoracic surgery appears to be rapid with most studies indicating the steepest improvement in operating time occurring in the initial 15-20 cases for thymectomy and 20-40 cases for anatomic lung resection. Existing data can guide a standardized robotic curriculum for rapid adaptation, and aid credentialing and quality monitoring for robotic thoracic surgery programs.

Keywords: Learning curve; Lobectomy; Robotic surgery; Segmentectomy; Thymectomy.