Neoadjuvant Therapy in Robotic Lung Surgery: Elevating Surgical Complexity Without Compromising Outcomes

机器人辅助肺部手术中的新辅助治疗:在不影响疗效的前提下提升手术难度

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Abstract

Background: Neoadjuvant therapy, particularly the combination of chemotherapy and immunotherapy, has become standard in treating locally advanced non-small cell lung cancer (NSCLC). While this approach improves pathologic responses, its effect on postoperative outcomes following robotic-assisted thoracic surgery (RATS) is not fully characterized. Objective: This study aimed to evaluate the impact of neoadjuvant therapy on postoperative outcomes in patients undergoing RATS for NSCLC, focusing on operative time, conversion rates to open surgery, and postoperative complications. Methods: A retrospective cohort analysis was performed on patients who underwent RATS for NSCLC between February 2019 and August 2024. Propensity score matching was utilized to balance preoperative characteristics between the groups. The primary outcomes compared were operative time, conversion rates to open surgery, and postoperative complications, with statistical significance defined as p < 0.05. Results: A total of 253 patients were included in the analysis, of whom 23 received neoadjuvant therapy (either chemotherapy or chemoimmunotherapy) and 230 did not. The neoadjuvant group had significantly longer operative times (250 min vs. 221 min, p = 0.001) but there were no significant differences in conversion rates to open surgery (8.7% vs. 3.9%, p = 0.5). However, the neoadjuvant group showed a higher incidence of prolonged air leaks (>5 days) (39.13% vs. 35.21%, p < 0.001). Other parameters, such as hospital stay and chest drainage duration, showed no statistically significant differences between the groups (p = 0.860 and p = 0.760, respectively). Conclusions: These findings support the feasibility of robotic-assisted thoracic surgery following neoadjuvant therapy in NSCLC, suggesting that this approach may be safely integrated into clinical practice for selected patients. Further studies are needed to define patient selection criteria and optimize postoperative management, potentially guiding personalized treatment strategies in complex cases.

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