Reshaping the Robotic Learning Curve: The Role of Prior Video-Assisted Thoracoscopic Surgery in Anatomic Lung Resection

Objectives The adoption of robotic-assisted thoracoscopic surgery for lung cancer has steadily increased; however, the learning curve and influence of prior video-assisted thoracoscopic surgery (VATS) experience remain underexplored. This study investigates the impact of prior VATS experience on the learning trajectory of robotic anatomic lung resection. Methods We retrospectively analyzed 341 robotic anatomic lung resection procedures performed between January 2018 and December 2024 at a single tertiary referral center. Three thoracic surgeons with varying VATS experience—A (1,500 cases), B (350 cases), and C (50 cases)—were included. Learning curves were assessed using cumulative sum analysis for operative time, complication rates, lymph node yield, and postoperative hospital stay. Change points were identified, and early versus late-phase outcomes were compared. Results All surgeons demonstrated significant reductions in operative time after reaching their respective cumulative sum thresholds (cases 54, 35, and 34 for Surgeons A, B, and C, respectively). While Surgeon A exhibited early procedural stability, Surgeons B and C showed more rapid improvement with experience. Lymph node yield increased significantly for Surgeon B (p = 0.002) and marginally for Surgeon C (p = 0.074). Complication rates and hospital stay modestly increased in later phases, likely reflecting greater case complexity. Conclusion Although prior VATS experience supports initial operative consistency, it does not necessarily shorten the robotic learning curve. Instead, case volume and intensity of robotic exposure appear more critical. These findings underscore the need for structured training programs emphasizing high case density and progressive complexity to optimize robotic surgical proficiency.