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Measurement of body mass by bioelectrical impedance analysis and computed tomography in cancer patients with malnutrition – a cross-sectional observational study
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 qua...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Lippincott Williams & Wilkins
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7738080/ https://www.ncbi.nlm.nih.gov/pubmed/33327343 http://dx.doi.org/10.1097/MD.0000000000023642 |
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author | Mueller, Tara Catharina Reik, Lilly Prokopchuk, Olga Friess, Helmut Martignoni, Marc Eric |
author_facet | Mueller, Tara Catharina Reik, Lilly Prokopchuk, Olga Friess, Helmut Martignoni, Marc Eric |
author_sort | Mueller, Tara Catharina |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7738080 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Lippincott Williams & Wilkins |
record_format | MEDLINE/PubMed |
spelling | pubmed-77380802020-12-16 Measurement of body mass by bioelectrical impedance analysis and computed tomography in cancer patients with malnutrition – a cross-sectional observational study Mueller, Tara Catharina Reik, Lilly Prokopchuk, Olga Friess, Helmut Martignoni, Marc Eric Medicine (Baltimore) 5500 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. Lippincott Williams & Wilkins 2020-12-11 /pmc/articles/PMC7738080/ /pubmed/33327343 http://dx.doi.org/10.1097/MD.0000000000023642 Text en Copyright © 2020 the Author(s). Published by Wolters Kluwer Health, Inc. http://creativecommons.org/licenses/by-nc/4.0 This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial License 4.0 (CCBY-NC), where it is permissible to download, share, remix, transform, and buildup the work provided it is properly cited. The work cannot be used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc/4.0 |
spellingShingle | 5500 Mueller, Tara Catharina Reik, Lilly Prokopchuk, Olga Friess, Helmut Martignoni, Marc Eric Measurement of body mass by bioelectrical impedance analysis and computed tomography in cancer patients with malnutrition – a cross-sectional observational study |
title | Measurement of body mass by bioelectrical impedance analysis and computed tomography in cancer patients with malnutrition – a cross-sectional observational study |
title_full | Measurement of body mass by bioelectrical impedance analysis and computed tomography in cancer patients with malnutrition – a cross-sectional observational study |
title_fullStr | Measurement of body mass by bioelectrical impedance analysis and computed tomography in cancer patients with malnutrition – a cross-sectional observational study |
title_full_unstemmed | Measurement of body mass by bioelectrical impedance analysis and computed tomography in cancer patients with malnutrition – a cross-sectional observational study |
title_short | Measurement of body mass by bioelectrical impedance analysis and computed tomography in cancer patients with malnutrition – a cross-sectional observational study |
title_sort | measurement of body mass by bioelectrical impedance analysis and computed tomography in cancer patients with malnutrition – a cross-sectional observational study |
topic | 5500 |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7738080/ https://www.ncbi.nlm.nih.gov/pubmed/33327343 http://dx.doi.org/10.1097/MD.0000000000023642 |
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