Postoperative pneumonia in patients with non-small cell lung cancer undergoing thoracoscopic surgery: What should we care about? - You, Jinzhi; Chen, Dandan; Liu, Xiang; Zhang, Hailing; Zheng, Zhongfeng (Frontiers in Oncology, 2025)
BackgroundThe prevention of postoperative pneumonia in patients with non-small cell lung cancer (NSCLC) undergoing thoracoscopic surgery holds significant clinical importance. This study aimed to evaluate the status quo and influencing factors of postoperative pneumonia in patients with NSCLC.MethodsPatients with NSCLC undergoing thoracoscopic surgery at our hospital from January 2023 to October 2024 were included. The characteristics of patients with and without postoperative pneumonia were analyzed. A logistic regression model was employed to analyze the influencing factors of postoperative pneumonia, and a corresponding predictive model was constructed. The predictive performance of the model was evaluated using receiver operating characteristic (ROC) curve analysis.ResultsA total of 226 patients with NSCLC were included, the incidence of postoperative pneumonia in patients with NSCLC was 31.86%. Correlation analyses showed that age(r=0.570), scope of the surgical procedure(r=0.618), COPD(r=0.562), history of smoking(r=0.516) and hypoproteinemia(r=0.587) were associated with the occurrence of postoperative pneumonia. Logistic regression analysis revealed that age (OR=2.146, 95%CI: 1.439~3.045), scope of the surgical procedure (OR=3.009, 95%CI: 2.813~3.543), COPD (OR=2.312, 95%CI: 1.605~3.008), history of smoking (OR=2.445, 95%CI: 2.117~2.821) and hypoproteinemia(OR=1.997, 95%CI: 1.533~2.580) were the independent influencing factors of postoperative pneumonia in patient with NSCLC. The area under the ROC curve (AUC) was 0.830.ConclusionThe incidence of postoperative pneumonia in patients with NSCLC is relatively high and is influenced by a multitude of factors. The postoperative pneumonia risk prediction model developed in this study has demonstrated promising predictive performance. However, given the single-center design and limited sample size, additional clinical validation is necessary to confirm its practical applicability and reliability in real-world clinical settings.