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The Predictive Value of Low Muscle Mass as Measured on CT Scans for Postoperative Complications and Mortality in Gastric Cancer Patients: A Systematic Review and Meta-Analysis

Risk assessment is relevant to predict outcomes in patients with gastric cancer. This systematic review aimed to investigate the predictive value of low muscle mass for postoperative complications in gastric cancer patients. A systematic literature search was performed to identify all articles repor...

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Autores principales: Borggreve, Alicia S., den Boer, Robin B., van Boxel, Gijs I., de Jong, Pim A., Veldhuis, Wouter B., Steenhagen, Elles, van Hillegersberg, Richard, Ruurda, Jelle P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7019480/
https://www.ncbi.nlm.nih.gov/pubmed/31940770
http://dx.doi.org/10.3390/jcm9010199
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author Borggreve, Alicia S.
den Boer, Robin B.
van Boxel, Gijs I.
de Jong, Pim A.
Veldhuis, Wouter B.
Steenhagen, Elles
van Hillegersberg, Richard
Ruurda, Jelle P.
author_facet Borggreve, Alicia S.
den Boer, Robin B.
van Boxel, Gijs I.
de Jong, Pim A.
Veldhuis, Wouter B.
Steenhagen, Elles
van Hillegersberg, Richard
Ruurda, Jelle P.
author_sort Borggreve, Alicia S.
collection PubMed
description Risk assessment is relevant to predict outcomes in patients with gastric cancer. This systematic review aimed to investigate the predictive value of low muscle mass for postoperative complications in gastric cancer patients. A systematic literature search was performed to identify all articles reporting on muscle mass as measured on computed tomography (CT) scans in patients with gastric cancer. After full text screening, 15 articles reporting on 4887 patients were included. Meta-analysis demonstrated that patients with low muscle mass had significantly higher odds of postoperative complications (odds ratio (OR): 2.09, 95% confidence interval (CI): 1.55–2.83) and severe postoperative complications (Clavien–Dindo grade ≥III, OR: 1.73, 95% CI: 1.14–2.63). Moreover, patients with low muscle mass had a significantly higher overall mortality (hazard ratio (HR): 1.81, 95% CI: 1.52–2.14) and disease-specific mortality (HR: 1.58, 95% CI: 1.36–1.84). In conclusion, assessment of muscle mass on CT scans is a potential relevant clinical tool for risk prediction in gastric cancer patients. Considering the heterogeneity in definitions applied for low muscle mass on CT scans in the included studies, a universal cutoff value of CT-based low muscle mass is required for more reliable conclusions.
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spelling pubmed-70194802020-03-09 The Predictive Value of Low Muscle Mass as Measured on CT Scans for Postoperative Complications and Mortality in Gastric Cancer Patients: A Systematic Review and Meta-Analysis Borggreve, Alicia S. den Boer, Robin B. van Boxel, Gijs I. de Jong, Pim A. Veldhuis, Wouter B. Steenhagen, Elles van Hillegersberg, Richard Ruurda, Jelle P. J Clin Med Review Risk assessment is relevant to predict outcomes in patients with gastric cancer. This systematic review aimed to investigate the predictive value of low muscle mass for postoperative complications in gastric cancer patients. A systematic literature search was performed to identify all articles reporting on muscle mass as measured on computed tomography (CT) scans in patients with gastric cancer. After full text screening, 15 articles reporting on 4887 patients were included. Meta-analysis demonstrated that patients with low muscle mass had significantly higher odds of postoperative complications (odds ratio (OR): 2.09, 95% confidence interval (CI): 1.55–2.83) and severe postoperative complications (Clavien–Dindo grade ≥III, OR: 1.73, 95% CI: 1.14–2.63). Moreover, patients with low muscle mass had a significantly higher overall mortality (hazard ratio (HR): 1.81, 95% CI: 1.52–2.14) and disease-specific mortality (HR: 1.58, 95% CI: 1.36–1.84). In conclusion, assessment of muscle mass on CT scans is a potential relevant clinical tool for risk prediction in gastric cancer patients. Considering the heterogeneity in definitions applied for low muscle mass on CT scans in the included studies, a universal cutoff value of CT-based low muscle mass is required for more reliable conclusions. MDPI 2020-01-11 /pmc/articles/PMC7019480/ /pubmed/31940770 http://dx.doi.org/10.3390/jcm9010199 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Borggreve, Alicia S.
den Boer, Robin B.
van Boxel, Gijs I.
de Jong, Pim A.
Veldhuis, Wouter B.
Steenhagen, Elles
van Hillegersberg, Richard
Ruurda, Jelle P.
The Predictive Value of Low Muscle Mass as Measured on CT Scans for Postoperative Complications and Mortality in Gastric Cancer Patients: A Systematic Review and Meta-Analysis
title The Predictive Value of Low Muscle Mass as Measured on CT Scans for Postoperative Complications and Mortality in Gastric Cancer Patients: A Systematic Review and Meta-Analysis
title_full The Predictive Value of Low Muscle Mass as Measured on CT Scans for Postoperative Complications and Mortality in Gastric Cancer Patients: A Systematic Review and Meta-Analysis
title_fullStr The Predictive Value of Low Muscle Mass as Measured on CT Scans for Postoperative Complications and Mortality in Gastric Cancer Patients: A Systematic Review and Meta-Analysis
title_full_unstemmed The Predictive Value of Low Muscle Mass as Measured on CT Scans for Postoperative Complications and Mortality in Gastric Cancer Patients: A Systematic Review and Meta-Analysis
title_short The Predictive Value of Low Muscle Mass as Measured on CT Scans for Postoperative Complications and Mortality in Gastric Cancer Patients: A Systematic Review and Meta-Analysis
title_sort predictive value of low muscle mass as measured on ct scans for postoperative complications and mortality in gastric cancer patients: a systematic review and meta-analysis
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7019480/
https://www.ncbi.nlm.nih.gov/pubmed/31940770
http://dx.doi.org/10.3390/jcm9010199
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