Exploring previously used thresholds for computed tomography‐defined low skeletal muscle mass in predicting functional limitations among lung cancer patients

Abstract

AbstractBackgroundVarious cutoffs have been used to diagnose computed tomography (CT)‐defined low skeletal muscle mass; however, the impact of this variability on predicting physical functional limitations (PFL) remains unclear. In the present study we aimed to evaluate the diagnostic test metrics for predicting PFLs using a fixed cutoff value from previous reports and sought to create a prediction score that incorporated the skeletal muscle index (SMI) and other clinical factors.MethodsIn this cross‐sectional study including 237 patients with lung cancer, the SMI was assessed using CT‐determined skeletal muscle area at the third lumbar vertebra. Physical function was assessed using the short physical performance battery (SPPB) test, with PFL defined as an SPPB score ≤9. We analyzed the diagnostic metrics of the five previous cutoffs for CT‐defined low skeletal muscle mass in predicting PFL.ResultsThe mean age of participants was 66.0 ± 10.4 years. Out of 237 patients, 158 (66.7%) had PFLs. A significant difference was observed in SMI between individuals with and without PFLs (35.7 cm2/m2 ± 7.8 vs. 39.5 cm2/m2 ± 8.4, p < 0.001). Diagnostic metrics of previous cutoffs in predicting PFL showed suboptimal sensitivity (63.29%–91.77%), specificity (11.39%–50.63%), and area under the receiver operating characteristic curve (AUC) values (0.516–0.592). Age and the SMI were significant predictors of PFL; therefore, a score for predicting PFL (age – SMI + 21) was constructed, which achieved an AUC value of 0.748.ConclusionFixed cutoffs for CT‐defined low skeletal muscle mass may inadequately predict PFLs, potentially overlooking declining physical functions in patients with lung cancer.