Usefulness of 18F-FDG PET/computed tomography metabolic parameters in predicting sarcopenia and prognosis of treatment-naive patients with non-small cell lung cancer

Abstract

Purpose Sarcopenia tremendously impacts the quality of life but remains debatable in prognostication in treatment-naive patients with non-small cell lung cancer (NSCLC). Hence, this study aimed to find a clinically feasible approach using 18F-FDG PET/computed tomography (CT) imaging parameters and clinical characteristics to predict sarcopenia and determine independent prognostic factors. Methods Clinical characteristics and 18F-FDG PET/CT metabolic parameters, including maximum standard uptake value, metabolic tumor volume, and total lesion glycolysis of primary tumor (SUVmax_P, MTV_P, and TLG_P) and combination of whole-body lesions (MTV_C and TLG_C) were collected in 344 treatment-naive patients with NSCLC. Skeletal muscle index at the third lumbar vertebra was calculated to determine sarcopenia. SUVmax of the psoas major muscle (SUVmax_M) was measured at the third lumbar vertebra as well. The diagnostic endpoint is the probability of sarcopenia, and the survival endpoints include progression-free survival (PFS) and overall survival (OS). Results Among 344 patients with NSCLC there were 271 patients with adenocarcinoma and 73 with squamous cell carcinoma (SCC). One hundred forty-seven patients (42.7%) were diagnosed with sarcopenia. Higher age, male, lower BMI, SCC, and lower SUVmax_M were correlated with a higher incidence of sarcopenia (P < 0.05), while age, sex and SUVmax_M were independently predictive of sarcopenia. Multivariate Cox-regression analysis revealed that BMI, advanced stage and TLG_C were independent predictors of PFS and OS, while sex was independently predictive of OS. Conclusions The incidence of sarcopenia increased with declining SUVmax of muscle. BMI, tumor stage, and TLG_C, but not sarcopenia, were found independently predictive of both PFS and OS.