Nutritional ultrasound cut off for predicting complications and mortality in lung cancer patients: a multicenter longitudinal study from the VALONC project

Introduction Lung cancer remains a leading cause of cancer-related mortality, often exacerbated by malnutrition and muscle depletion that traditional weight-centric metrics may fail to identify. This study assessed the clinical and prognostic relevance of rectus femoris (RF) ultrasound as a practical bedside tool for evaluating muscle-related parameters and clinical outcomes. Methods This multicenter longitudinal study involved 374 patients (114 females, 260 males) across 10 Spanish hospitals. Researchers performed ultrasonographic assessments of the RF, measuring cross-sectional area (RF-CSA), thickness ( Y -axis), and circumference, alongside GLIM malnutrition criteria and PG-SGA. Statistical analyses included Random Forest algorithms, ROC curves, and Cox regression models adjusted for age, BMI, ECOG performance status, cancer type, and cancer stage to determine sex-specific associations with clinical outcomes. Results Significant sexual dimorphism was observed; men exhibited larger muscle parameters, while women had higher subcutaneous fat. RF-CSA and RF- Y -axis showed the highest discriminative performance for GLIM-defined malnutrition, with AUCs of 0.706 and 0.713 in men and 0.814 and 0.804 in women, respectively. The corresponding RF-CSA cut-offs were 3.88 cm 2 in men and 2.78 cm 2 in women, whereas RF- Y -axis cut-offs were 1.09 cm in men and 0.95 cm in women. In men, RF- Y -axis was significantly associated with all-cause mortality (HR = 0.32, 95% CI: 0.15–0.71), whereas RF-CSA, RF-CIR, and RF- X -axis were associated with clinical complications. No significant associations with mortality or complications were observed in women. A moderate agreement was observed between GLIM and PG-SGA (weighted κ = 0.51), suggesting that these criteria capture overlapping but not identical dimensions of malnutrition. Discussion Rectus femoris ultrasound may provide objective, sex-specific clinical information that complements the GLIM framework and traditional anthropometric assessments. By identifying clinically relevant muscle waste, this bedside tool allows for the early detection of high-risk patients, potentially directing timely nutritional and rehabilitative interventions to improve survival and treatment tolerance in lung cancer.