Association between low muscle mass assessed by bioelectrical impedance analysis and clinical outcomes in hospitalized cancer patients.

Abstract

11034 Background: Low muscle mass is an independent prognostic marker associated with increased clinical risk, functional impairment, and mortality in patients with cancer. Conventional indicators such as body mass index (BMI) may fail to identify individuals at nutritional and functional risk. Bioelectrical impedance analysis (BIA) offers a feasible bedside method for body composition assessment, particularly in resource-constrained hospital settings. This study aimed to evaluate body composition using BIA, determine the prevalence of low muscle mass, and examine its association with clinical, laboratory, and functional parameters in hospitalized oncology patients. Methods: This observational study included 104 adult cancer patients admitted to a tertiary public hospital between January and October 2025. Baseline assessments at hospital admission included BMI, skeletal muscle mass index (SMI), appendicular muscle index, phase angle, fat mass percentage, handgrip strength (HGS), calf circumference (CC), urea-to-creatinine ratio, length of hospital stay, and in-hospital outcome (discharge or death). Low muscle mass was defined according to established cutoffs for SMI and appendicular muscle index. Comparisons were performed between patients with and without low muscle mass, and correlations between appendicular muscle index and functional and nutritional parameters were analyzed. Results: Low muscle mass was identified in 29.8% of patients at admission. Compared with patients without low muscle mass, those affected had significantly lower BMI (23.3 vs 27.6 kg/m², p=0.001), appendicular muscle index (6.20 vs 7.61, p<0.001), phase angle (3.6° vs 5.1°, p<0.001), total muscle mass (25.1 vs 29.4 kg, p<0.001), HGS (30.0 vs 37.0 kgf, p=0.041), and CC (32.5 vs 37.0 cm, p<0.001). Length of hospital stay did not differ significantly between groups. In-hospital mortality was higher among patients with low muscle mass (18.5% vs 7.0%), although this difference did not reach statistical significance (p=0.133). Appendicular muscle index showed moderate to strong positive correlations with BMI, phase angle, HGS, CC, and SMI. Conclusions: BIA proved to be a feasible and informative tool for identifying low muscle mass and functional impairment in hospitalized cancer patients. Appendicular muscle index and SMI were superior to BMI in detecting patients at increased nutritional and functional risk. Given its low cost and bedside applicability, BIA represents a valuable strategy for early risk stratification and supportive care planning in resource-limited oncology settings.