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Resting energy expenditure in the risk assessment of anticancer treatments

Authors :
Jérôme Alexandre
Jean Philippe Durand
François Goldwasser
Luc Cynober
Nathalie Neveux
Anne Jouinot
Romain Coriat
Olivier Huillard
Jean Pascal De Bandt
Clara Vazeille
Pascaline Boudou-Rouquette
Jeanne Chapron
Source :
Clinical Nutrition. 37:558-565
Publication Year :
2018
Publisher :
Elsevier BV, 2018.

Abstract

Alterations of nutritional and performance status (PS) are associated with higher risk of chemotherapy toxicity. Increased resting energy expenditure (REE) is frequent in cancer patients and may contribute to cachexia. We investigated whether abnormal energetic metabolism could predict early acute limiting toxicities (ELT) of anticancer treatments.In this observational monocentric study, REE was measured by indirect calorimetry before treatment initiation. Based on the ratio of measured REE to REE predicted by the Harris-Benedict formula, patients were classified as hypometabolic (90%), normometabolic (90-110%) or hypermetabolic (110%). Body mass index, weight loss, PS, albumin, transthyretin, C-reactive protein (CRP) and muscle mass (CT-scan) were studied. Were defined as ELT any unplanned hospitalization or any adverse event leading to dose reduction or discontinuation during the first cycle of treatment.We enrolled 277 patients: 76% had metastatic disease; 89% received chemotherapy and 11% targeted therapy; 29% were normometabolic, 51% hypermetabolic and 20% hypometabolic. Fifty-nine patients (21%) experienced an ELT. Toxicity was associated with abnormal metabolism (vs normal: OR = 2.37 [1.13-4.94], p = 0.023), PS (2-3 vs 0-1: OR = 2.04 [1.12-3.74], p = 0.023), albumin (35 vs ≥35 g/l: OR = 2.39 [1.03-5.54], p = 0.048), and inflammation (CRP ≥10 vs10 mg/l: OR = 2.43 [1.35-4.38], p = 0.004). To predict toxicity, the most sensitive parameter was the REE (83%) followed by PINI (63%), GPS (59%), CRP (55%), PS (41%), NRI (37%), and albumin (16%). In multivariate analysis, elevated CRP was an independent predictor of toxicity (p = 0.047).Abnormal basal energy metabolism identifies patients at higher risk of treatment-related acute complications.

Details

ISSN :
02615614
Volume :
37
Database :
OpenAIRE
Journal :
Clinical Nutrition
Accession number :
edsair.doi.dedup.....0a0800b8db07c2463b17edf984dc7368
Full Text :
https://doi.org/10.1016/j.clnu.2017.01.007