Background: Robotic-assisted thoracic surgery (RATS) and video-assisted thoracoscopic surgery (VATS) are prominent techniques in minimally invasive anatomic lung resections. Understanding their learning curves is essential for surgical training, credentialing, and patient safety. However, consistent definitions of learning curve phases remain lacking. This systematic review and meta-analysis aimed to compare the learning curves of RATS and VATS performed by the same surgeon or team, define proficiency thresholds, and evaluate clinical outcomes. Methods: A systematic review and meta-analysis were conducted for studies published between 1998 and 2025. Included studies used validated learning curve methods (e.g., CUSUM analysis) and directly compared RATS and VATS by the same surgeon or surgical team. Six retrospective studies met inclusion criteria. Primary outcomes were the number of cases needed to reach proficiency and operative time. Secondary outcomes included complication rates, conversion rates, chest tube duration, hospital stay, and lymph node yield. Meta-analyses used random-effects models. Results: The mean number of cases to achieve proficiency was 27.5 for RATS and 33.7 for VATS (p = 0.38). No significant differences were found in operative time (mean difference – 2.89 minutes; 95% CI –11.01 to 5.23; p = 0.4851), complication rates (OR = 1.05; 95% CI: 0.60 to 1.84; p = 0.86), or conversion rates (OR = 0.53; 95% CI: 0.17 to 1.65; p = 0.32). Chest tube duration also showed no significant difference (mean difference –1,78 days; 95% CI – 3,99 to 0.44; p = 0.1157). However, RATS was associated with a significantly shorter hospital stay (mean difference –0.99 days; 95% CI –1.90 to –0.09; p = 0.0315; I² = 86.3%). Conclusion: RATS and VATS have comparable learning curves and perioperative outcomes. Although not statistically significant, the slightly lower case threshold suggests RATS may be adopted earlier. Standardised learning curve definitions are essential for safe and effective surgical training and implementation.
Ηλίας Αρφάνης (Wed,) studied this question.