Abstract
BACKGROUND: The predictive value of body composition and inflammatory parameters in patients with resectable non-small cell lung cancer (NSCLC) undergoing neoadjuvant chemoimmunotherapy remains poorly defined. The study sought to evaluate the association between computed tomography (CT)-based body composition, inflammatory markers, and survival outcomes in NSCLC patients following neoadjuvant chemoimmunotherapy. METHODS: This retrospective study included resectable NSCLC patients undergoing neoadjuvant chemoimmunotherapy from June 2019 to March 2023. CT images were collected at three levels (T4, T10, and L1) for quantifying skeletal muscle and adipose tissue. Blood routine results were collected to calculate inflammatory parameters. All measurements were obtained at baseline and preoperatively. Kaplan-Meier survival curves were plotted and compared using the log-rank tests. Cox regression analysis was performed to investigate the predictive value of clinical, inflammatory, and body composition parameters for disease-free survival (DFS). RESULTS: A total of 154 patients were included, with 21 (13.6%) deaths and 27 (17.5%) experienced recurrence or metastasis. Major pathological response (MPR) was observed in 71 (46.1%) patients. Multivariate analysis identified MPR and treatment time as independent clinical predictors of DFS. In body composition analysis, baseline subcutaneous adipose tissue area at L1, subcutaneous adipose tissue density at T10, pectoral muscle density (PMD) at T4, and delta-PMD at T4 demonstrated predictive value for DFS. Baseline inflammatory markers, including neutrophil-to-lymphocyte ratio and systemic immune inflammation index, were also associated with DFS. A comprehensive model integrating clinical, body composition, and inflammatory parameters demonstrated superior prognostic performance with the receiver operating characteristic areas under the curve for DFS at 1-, 2-, and 3-year of 0.832, 0.806 and 0.797, respectively. CONCLUSIONS: Baseline body composition and inflammation parameters were valuable in predicting DFS, while preoperative parameters had limited prognostic value. A combined model integrating clinical, body composition, and inflammatory parameters demonstrated enhanced predictive performance for DFS, and may serve as a valuable tool for assessing prognosis in resectable NSCLC patients undergoing neoadjuvant chemoimmunotherapy.