Abstract
OBJECTIVE: Chronic post-surgical pain (CPSP) following thoracoscopic lung cancer surgery is a common and challenging complication. Identifying risk factors and predictive markers is essential for improving patient outcome. METHODS: In this retrospective case-control study, the clinical data from 106 patients with non-small cell lung cancer (NSCLC) who underwent thoracoscopic radical resection between January 2021 and December 2023 were comprehensively analyzed. Patients were divided into a CPSP group (n = 41) and a non-CPSP group (n = 65) based on CPSP status. An external validation cohort of 20 patients was also assessed. Demographic data, perioperative characteristics, psychological states, and pain scores were compared between the two groups. Logistic regression analysis was used to identify predictors of CPSP, and their predictive performance was validated using receiver operating characteristic (ROC) curve analysis. RESULTS: Age and TNM stage were significantly higher in the CPSP group (P < 0.001). Significant differences were observed in pain scores on postoperative days 1-3 and Fear of Pain Questionnaire-III (FPQ-III) scores (P = 0.003 and P < 0.001, respectively) between the two groups. Multivariate logistic regression identified age (OR, 1.230; P < 0.001), TNM staging (OR, 5.106; P < 0.001), early postoperative pain score (OR, 1.868; P = 0.012), and FPQ-III score (OR, 1.135; P < 0.001) as independent predictors of CPSP. A nomogram based on these predictors demonstrated excellent discrimination ability, with an area under the curve (AUC) of 0.891. External validation yielded an AUC of 0.956, confirming high sensitivity (1.00) and specificity (0.923). CONCLUSION: Age, advanced TNM stage, early postoperative pain intensity, and higher fear of pain are significant predictors of chronic postoperative pain following thoracoscopic lung cancer surgery. Incorporating these factors into predictive models may improve postoperative management and reduce CPSP incidence.