Evaluating predictive equations for energy requirements throughout breast cancer trajectory: A comparative study.

Breast cancer Energy expenditure Energy metabolism Indirect calorimetry Predictive equations Whole-room indirect calorimeter

Journal

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

Informations de publication

Date de publication:
26 Jul 2024
Historique:
received: 12 06 2024
revised: 24 07 2024
accepted: 25 07 2024
medline: 3 8 2024
pubmed: 3 8 2024
entrez: 2 8 2024
Statut: aheadofprint

Résumé

Accurately estimating resting energy requirements is crucial for optimizing energy intake, particularly in the context of patients with varying energy needs, such as individuals with cancer. We sought to evaluate the agreement between resting energy expenditure (REE) predicted by 40 equations and that measured by reference methods in women undergoing active breast cancer treatment stage (I-IV) and post-completion (i.e., survivors). Data from 4 studies were combined. REE values estimated from 40 predictive equations identified by a systematic search were compared with REE assessed by indirect calorimetry (IC) using a metabolic cart (MC-REE N = 46) or a whole-room indirect calorimeter (WRIC-REE N = 44). Agreement between methods was evaluated using Bland-Altman and Lin's concordance coefficient correlation (Lin's CCC). Ninety participants (24 % survivors, 61.1% had early-stage breast cancer I or II, mean age: 56.8 ± 11 years; body mass index: 28.7 ± 6.4 kg/m Most equations failed to accurately predict REE at the group level, and none were effective at the individual level. This inaccuracy has significant implications for women with or surviving breast cancer, who may experience weight gain, maintenance, or loss due to inaccurate energy needs estimations. Therefore, our research underscores the need for further efforts to improve REE estimation.

Sections du résumé

BACKGROUND & AIMS OBJECTIVE
Accurately estimating resting energy requirements is crucial for optimizing energy intake, particularly in the context of patients with varying energy needs, such as individuals with cancer. We sought to evaluate the agreement between resting energy expenditure (REE) predicted by 40 equations and that measured by reference methods in women undergoing active breast cancer treatment stage (I-IV) and post-completion (i.e., survivors).
METHODS METHODS
Data from 4 studies were combined. REE values estimated from 40 predictive equations identified by a systematic search were compared with REE assessed by indirect calorimetry (IC) using a metabolic cart (MC-REE N = 46) or a whole-room indirect calorimeter (WRIC-REE N = 44). Agreement between methods was evaluated using Bland-Altman and Lin's concordance coefficient correlation (Lin's CCC).
RESULTS RESULTS
Ninety participants (24 % survivors, 61.1% had early-stage breast cancer I or II, mean age: 56.8 ± 11 years; body mass index: 28.7 ± 6.4 kg/m
CONCLUSION CONCLUSIONS
Most equations failed to accurately predict REE at the group level, and none were effective at the individual level. This inaccuracy has significant implications for women with or surviving breast cancer, who may experience weight gain, maintenance, or loss due to inaccurate energy needs estimations. Therefore, our research underscores the need for further efforts to improve REE estimation.

Identifiants

pubmed: 39094472
pii: S0261-5614(24)00259-0
doi: 10.1016/j.clnu.2024.07.032
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

2073-2082

Informations de copyright

Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.

Déclaration de conflit d'intérêts

Conflict of interest C.M.P. reports receiving unrelated honoraria and/or paid consultancy from Abbott Nutrition, Nutricia, Nestle Health Science, Pfizer, and AMRA Medical. B.R.S, A.P.P, A.A.K, M.C.G, M.J.H, A.A.J, P.S, E.C, I.P, E.P and R.T. declare no conflicts of interest.

Auteurs

Bruna R da Silva (BR)

Human Nutrition Research Unit, Department of Agricultural, Food & Nutritional Science, University of Alberta, Edmonton, Alberta, Canada.

Ana Paula Pagano (AP)

Human Nutrition Research Unit, Department of Agricultural, Food & Nutritional Science, University of Alberta, Edmonton, Alberta, Canada.

Amy A Kirkham (AA)

Faculty of Kinesiology and Physical Education, University of Toronto, Toronto, Ontario, Canada.

Maria Cristina Gonzalez (MC)

Postgraduate Program in Health and Behavior, Catholic University of Pelotas, Pelotas, State of Rio Grande do Sul, Brazil.

Mark J Haykowsky (MJ)

Faculty of Nursing, University of Alberta, Edmonton, Alberta, Canada.

Anil A Joy (AA)

Division of Medical Oncology, Department of Oncology, University of Alberta Edmonton, Alberta, Canada.

Karen King (K)

Division of Medical Oncology, Department of Oncology, University of Alberta Edmonton, Alberta, Canada.

Pierre Singer (P)

Department of General Intensive Care and Institute for Nutrition Research, Rabin Medical Center, Beilinson Hospital, Sackler School of Medicine, Tel Aviv University, Israel.

Emanuele Cereda (E)

Clinical Nutrition and Dietetics Unit, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy.

Ian Paterson (I)

Department of Medicine, Division of Cardiology, University of Ottawa, Ontario, Canada.

Edith Pituskin (E)

Faculty of Nursing, University of Alberta, Edmonton, Alberta, Canada.

Richard Thompson (R)

Department of Biomedical Engineering, University of Alberta, Edmonton, Alberta, Canada.

Carla M Prado (CM)

Human Nutrition Research Unit, Department of Agricultural, Food & Nutritional Science, University of Alberta, Edmonton, Alberta, Canada. Electronic address: carla.prado@ualberta.ca.

Classifications MeSH