Muscle matters: Prognostic implications of malnutrition and muscle health parameters in patients with cancer. A secondary analysis of a randomised trial.

CT Cancer GLIM Malnutrition Muscle Sarcopenia

Journal

Clinical nutrition (Edinburgh, Scotland)
ISSN: 1532-1983
Titre abrégé: Clin Nutr
Pays: England
ID NLM: 8309603

Informations de publication

Date de publication:
02 Aug 2024
Historique:
received: 28 03 2024
revised: 18 06 2024
accepted: 18 07 2024
medline: 26 8 2024
pubmed: 26 8 2024
entrez: 24 8 2024
Statut: aheadofprint

Résumé

Low muscle mass and malnutrition are independently associated with an increased risk of adverse outcomes in patients with cancer. However, it is not yet clear which parameter is most indicative of these risks. This study investigates the prognostic significance of different parameters reflecting malnutrition and muscle health in a well-characterised oncology population at nutritional risk. This preplanned secondary analysis included patients with cancer from a Swiss-wide, randomised-controlled nutritional trial. We investigated associations among malnutrition markers (i.e., malnutrition diagnosis based on modified Global Leadership Initiative on Malnutrition (GLIM) criteria, albumin concentration) and muscle health markers (i.e., hand grip strength, computed tomography (CT)-based muscle mass and radiodensity) with 180-day all-cause mortality (primary outcome). We included 269 patients with a main admission diagnosis of cancer and available CT scans. In a mutually adjusted model, four parameters contributed to risk assessment including modified malnutrition diagnosis (GLIM) (HR 1.78 (95%CI 1.17 to 2.69), p = 0.007, AUC 0.58), low albumin concentration (HR 1.58 (95%CI 1.08 to 2.31), p = 0.019, AUC 0.62), low handgrip strength (HR 2.05 (95%CI 1.43 to 2.93), p = 0.001, AUC 0.62) and low muscle radiodensity (HR 1.39 (95%CI 0.90 to 2.16), p = 0.139, AUC 0.63). Combining these parameters resulted in a model with high prognostic power regarding 180-day mortality (overall AUC 0.71). In this study of inpatients with cancer at nutritional risk, several malnutrition and muscle health parameters emerged as independent prognostic indicators for mortality. The use of these parameters may improve risk stratification and guide nutritional interventions in this vulnerable population. ClinicalTrials.gov, number NCT02517476.

Sections du résumé

BACKGROUND BACKGROUND
Low muscle mass and malnutrition are independently associated with an increased risk of adverse outcomes in patients with cancer. However, it is not yet clear which parameter is most indicative of these risks. This study investigates the prognostic significance of different parameters reflecting malnutrition and muscle health in a well-characterised oncology population at nutritional risk.
METHODS METHODS
This preplanned secondary analysis included patients with cancer from a Swiss-wide, randomised-controlled nutritional trial. We investigated associations among malnutrition markers (i.e., malnutrition diagnosis based on modified Global Leadership Initiative on Malnutrition (GLIM) criteria, albumin concentration) and muscle health markers (i.e., hand grip strength, computed tomography (CT)-based muscle mass and radiodensity) with 180-day all-cause mortality (primary outcome).
RESULTS RESULTS
We included 269 patients with a main admission diagnosis of cancer and available CT scans. In a mutually adjusted model, four parameters contributed to risk assessment including modified malnutrition diagnosis (GLIM) (HR 1.78 (95%CI 1.17 to 2.69), p = 0.007, AUC 0.58), low albumin concentration (HR 1.58 (95%CI 1.08 to 2.31), p = 0.019, AUC 0.62), low handgrip strength (HR 2.05 (95%CI 1.43 to 2.93), p = 0.001, AUC 0.62) and low muscle radiodensity (HR 1.39 (95%CI 0.90 to 2.16), p = 0.139, AUC 0.63). Combining these parameters resulted in a model with high prognostic power regarding 180-day mortality (overall AUC 0.71).
CONCLUSIONS CONCLUSIONS
In this study of inpatients with cancer at nutritional risk, several malnutrition and muscle health parameters emerged as independent prognostic indicators for mortality. The use of these parameters may improve risk stratification and guide nutritional interventions in this vulnerable population.
TRIAL REGISTRATION BACKGROUND
ClinicalTrials.gov, number NCT02517476.

Identifiants

pubmed: 39181036
pii: S0261-5614(24)00249-8
doi: 10.1016/j.clnu.2024.07.020
pii:
doi:

Banques de données

ClinicalTrials.gov
['NCT02517476']

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

2255-2262

Informations de copyright

Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Déclaration de conflit d'intérêts

Conflict of interest The Institution of P.Schuetz has previously received unrestricted grant money unrelated to this project from Nestle Health Science and Abbott Nutrition. The institution of Z.Stanga received speaking honoraria and research support from Nestle Health Science, Abbott Nutrition and Fresenius Kabi. CMP has received honoraria and/or paid consultancy from Abbott Nutrition, Nutricia, Nestlé Health Science, Pfizer, and AMRA Medical. CMP has a conflict of interest with Dr. Vickie Baracos and Dr. Lisa Martin, who are both from the same institution. All other authors report no conflicts of interest. The results presented in this paper have not been published previously in whole or part, except in abstract form.

Auteurs

T Olpe (T)

Medical Faculty of the University of Basel, Basel, Switzerland.

C Wunderle (C)

Medical University Department, Division of General Internal and Emergency Medicine, Kantonsspital Aarau, Aarau, Switzerland.

L Bargetzi (L)

Medical Faculty of the University of Basel, Basel, Switzerland; Medical University Department, Division of General Internal and Emergency Medicine, Kantonsspital Aarau, Aarau, Switzerland.

P Tribolet (P)

Medical University Department, Division of General Internal and Emergency Medicine, Kantonsspital Aarau, Aarau, Switzerland; Department of Health Professions, Bern University of Applied Sciences, Bern, Switzerland; Department of Nutritional Sciences and Research Platform Active Ageing, University of Vienna, Vienna, Austria.

A Laviano (A)

Department of Translational and Precision Medicine, Sapienza University, Rome, Italy.

Z Stanga (Z)

Division of Diabetes, Endocrinology, Nutritional Medicine & Metabolism, Bern University Hospital and University of Bern, Bern, Switzerland.

C M Prado (CM)

Department of Agricultural, Food & Nutritional Science, University of Alberta, Edmonton, Canada.

B Mueller (B)

Medical Faculty of the University of Basel, Basel, Switzerland; Medical University Department, Division of General Internal and Emergency Medicine, Kantonsspital Aarau, Aarau, Switzerland.

P Schuetz (P)

Medical Faculty of the University of Basel, Basel, Switzerland; Medical University Department, Division of General Internal and Emergency Medicine, Kantonsspital Aarau, Aarau, Switzerland. Electronic address: philipp.schuetz@ksa.ch.

Classifications MeSH