Anne Jouinot1, Clara Vazeille2, Jean Philippe Durand2, Olivier Huillard2, Pascaline Boudou-Rouquette2, Romain Coriat3, Jeanne Chapron4, Nathalie Neveux5, Jean Pascal De Bandt5, Jerome Alexandre2, Luc Cynober5, Francois Goldwasser2. 1. Medical Oncology Department, Cancer Research for Personalized Medicine (CARPEM), Paris Centre Teaching Hospitals, Paris Descartes University, USPC, Paris, France. Electronic address: anne.jouinot@aphp.fr. 2. Medical Oncology Department, Cancer Research for Personalized Medicine (CARPEM), Paris Centre Teaching Hospitals, Paris Descartes University, USPC, Paris, France. 3. Gastro-Enterology Department, Paris Centre Teaching Hospitals, AP-HP, Paris Descartes University, USPC, Paris, France. 4. Pneumology Department, Paris Centre Teaching Hospitals, AP-HP, Paris Descartes University, USPC, Paris, France. 5. Clinical Chemistry, Paris Centre Teaching Hospitals, AP-HP, Paris Descartes University, USPC, Paris, France; EA 4466 PRETRAM, Pharmacy Faculty, Paris Descartes University, USPC, Paris, France.
Abstract
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.
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 cancerpatients 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.
Authors: Paolo Cotogni; Federico Bozzetti; François Goldwasser; Paula Jimenez-Fonseca; Sine Roelsgaard Obling; Juan W Valle Journal: Ther Adv Med Oncol Date: 2022-09-26 Impact factor: 5.485