Skeletal muscle depletion during neoadjuvant chemoimmunotherapy predicts postoperative complications in non-small
Wei Feng1,2, Xin Wang1,3, Heng Du1,2
1Department of Thoracic Surgery, West China Hospital, Sichuan University, Chengdu, China.
Background:
For patients with resectable locally advanced non-small cell lung cancer (NSCLC), surgical resection preceded by neoadjuvant chemoimmunotherapy (nICT) has become the standard treatment strategy. However, the triple physiological burden imposed by chemotherapy, immunotherapy, and ongoing tumor metabolism may compromise functional reserve and increase surgical risk. Identifying patients at high risk for postoperative complications remains a critical challenge in perioperative management. This study aimed to characterize dynamic changes in skeletal muscle and adipose tissue during nICT, to identify independent predictors of postoperative complications, and to evaluate the incremental predictive value of dynamic body composition metrics over established clinical variables.
Methods:
This retrospective study included 160 patients with resectable NSCLC who underwent surgical resection following nICT between June 2024 and December 2025. Skeletal muscle index (SMI), skeletal muscle density (SMD), visceral adipose tissue (VAT), and subcutaneous adipose tissue (SAT) were quantified at the L3 vertebral level on computed tomography (CT) images obtained before and after treatment. Dynamic changes (Δ) were calculated as the difference between pre-treatment and post-treatment values. The primary outcome was postoperative complications of Clavien-Dindo (CD) grade ≥II. Three predictive models were constructed and compared using area under the receiver operating characteristic curve (AUC), net reclassification improvement (NRI), and integrated discrimination improvement (IDI).
Results:
Following nICT, skeletal muscle metrics decreased significantly (median ΔSMI, -0.54 cm2/m2; P=0.01; median ΔSMD, -0.90 HU; P=0.003), while adipose tissue areas increased significantly (median ΔVAT, 9.54 cm2; P<0.001; median ΔSAT, 8.06 cm2; P<0.001). No significant correlation was observed between ΔSMI and ΔVAT (Spearman ρ=0.087; P=0.27), indicating divergent and independent metabolic trajectories. Of 160 patients, 58 (36.3%) developed CD grade ≥ II complications. Among the four dynamic body-composition measures, each evaluated in a separate multivariable model, only ΔSMI remained significantly associated with postoperative complications [adjusted odds ratio (OR) =0.806; 95% confidence interval (CI): 0.721-0.900; P<0.001], whereas ΔSMD, ΔVAT, and ΔSAT did not. Traditional assessments, including body mass index (BMI) change, Eastern Cooperative Oncology Group (ECOG) performance status, pulmonary function, and systemic inflammatory and nutritional indices, likewise showed no significant associations. Adding ΔSMI to the clinical model significantly improved AUC from 0.595 to 0.710 (ΔAUC =0.115; P=0.007).
Conclusions:
Dynamic loss of skeletal muscle during nICT, as assessed on routine CT images, was independently associated with postoperative complications in patients with resectable NSCLC. Compared with baseline body-composition parameters and conventional clinical indices, longitudinal change in SMI (ΔSMI) provided better discrimination of perioperative risk. Because ΔSMI can be derived from CT scans already obtained for treatment-response assessment, it may serve as a practical, low-burden imaging biomarker to support preoperative risk stratification and identify patients who may benefit from targeted prehabilitation.