BACKGROUND: We aimed to evaluate the agreement between computed tomography (CT) and surrogate methods applied in clinical practice for the assessment of low muscle mass. In addition, we assessed the association between different muscle-assessment methods and nutrition status, as well as the prognostic value of low muscle mass on survival in patients with colorectal cancer (CRC). METHODS: This is a cohort including 188 CRC patients with 17 months' follow-up (interquartile range: 12-23 months) for mortality. Low muscle mass was evaluated by corrected mid-upper arm muscle area (AMAc) and calf circumference, skeletal muscle mass by bioelectrical impedance analysis (BIA), muscle deficit by physical examination with the Patient-Generated Subjective Global Assessment (PG-SGA), and lumbar muscle cross-sectional area by CT (reference method). RESULTS: The prevalence of low muscle mass ranged from 9.6% to 54.3% according to the method used. The physical examination had the highest κ coefficient compared with CT. Low muscularity was associated with the presence of malnutrition, lower body fat, and low phase angle. The Cox regression models-adjusted for age, sex, and treatment 3 months before study inclusion-showed that severe muscle loss measured by BIA and CT and low muscle mass measured by PG-SGA predicted higher mortality rates. CONCLUSIONS: Compared with CT, the physical examination had the best agreement to assess low muscle mass. Low muscle mass assessed by PG-SGA, BIA, and CT showed similar prognostic values for survival.
BACKGROUND: We aimed to evaluate the agreement between computed tomography (CT) and surrogate methods applied in clinical practice for the assessment of low muscle mass. In addition, we assessed the association between different muscle-assessment methods and nutrition status, as well as the prognostic value of low muscle mass on survival in patients with colorectal cancer (CRC). METHODS: This is a cohort including 188 CRCpatients with 17 months' follow-up (interquartile range: 12-23 months) for mortality. Low muscle mass was evaluated by corrected mid-upper arm muscle area (AMAc) and calf circumference, skeletal muscle mass by bioelectrical impedance analysis (BIA), muscle deficit by physical examination with the Patient-Generated Subjective Global Assessment (PG-SGA), and lumbar muscle cross-sectional area by CT (reference method). RESULTS: The prevalence of low muscle mass ranged from 9.6% to 54.3% according to the method used. The physical examination had the highest κ coefficient compared with CT. Low muscularity was associated with the presence of malnutrition, lower body fat, and low phase angle. The Cox regression models-adjusted for age, sex, and treatment 3 months before study inclusion-showed that severe muscle loss measured by BIA and CT and low muscle mass measured by PG-SGA predicted higher mortality rates. CONCLUSIONS: Compared with CT, the physical examination had the best agreement to assess low muscle mass. Low muscle mass assessed by PG-SGA, BIA, and CT showed similar prognostic values for survival.