Measurement of body mass by bioelectrical impedance analysis and computed tomography in cancer patients with malnutrition – a cross-sectional observational study. Issue 50 (11th December 2020) - Mueller, Tara Catharina; Reik, Lilly; Prokopchuk, Olga; Friess, Helmut; Martignoni, Marc Eric
Abstract : Abstract: Malnutrition and cachexia affects the majority of cancer patients and significantly worsens their quality of life and prognosis. However, the diagnostic criteria of malnutrition and cachexia remain a topic under constant debate. To overcome this hurdle, diagnostic tools to objectively detect and quantify the loss of muscle and fat mass are needed. Computed tomography (CT)-based measurement is currently considered the golden standard. Bioelectrical impedance analysis (BIA) is an economical, non-invasive tool but it is seen controversial in patients with cancer and malnutrition because of possible estimation errors. BIA and CT-based analysis of body mass compartments were performed 172 times in 118 cancer patients, within the nutrition program of our institution. Prevalence of malnutrition was determined according to the global leadership initiative on malnutrition criteria. Data obtained for muscle and fat mass from both BIA and CT were correlated using Pearson's ρ . All analyses were performed with an explorative significance level of 5%. 45.7% of the cohort were classified as "malnourished." No significant differences were observed between the 2 groups regarding demographic data. Median body mass index, Karnofsky performance status, and nutritional risk score were lower in the malnourished group. Values for muscle and fat mass by BIA and CT were significantly lower in malnourished patients. Correlation of the measured parameters were highly significant between CT-based and BIA measurement. In the overall cohort, correlation of measured muscle mass values by CT and BIA was significant with Pearson's ρ  = 0.794 ( P  < .01). Looking at patients without malnutrition only, Pearson's ρ was 0.754 ( P  < .01). The correlation of measured fat mass values was equally significant, with Pearson's ρ of 0.748 ( P  < .01) in the overall cohort and 0.771 ( P  < .01) in patients with malnutrition. To our knowledge, this is the first study comparing BIA to CT-based body mass analysis in a large cohort of cancer patients with malnutrition. The results suggest that BIA is a valid diagnostic tool for the assessment of muscle and fat mass, even in patients with malnutrition, and could be implemented for the early detection and short-term follow-up of malnutrition and cachexia.