Clinical nutrition (Edinburgh, Scotland) · 2017
Resting energy expenditure in the risk assessment of anticancer treatments.
СтатьяНаблюдательное исследованиеНазвание и аннотация: Перевод в очереди
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Jouinot Anne, Vazeille Clara, Durand Jean Philippe, Huillard Olivier, Boudou-Rouquette Pascaline, Coriat Romain, Chapron Jeanne, Neveux Nathalie, De Bandt Jean Pascal, Alexandre Jerome, Cynober Luc, Goldwasser Francois
Аннотация
BACKGROUND & AIMS: 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.
METHODS: 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.
RESULTS: 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 vs <10 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).
CONCLUSION: Abnormal basal energy metabolism identifies patients at higher risk of treatment-related acute complications.
METHODS: 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.
RESULTS: 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 vs <10 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).
CONCLUSION: Abnormal basal energy metabolism identifies patients at higher risk of treatment-related acute complications.