Medical Oncology Department, Cancer Research for Personalized Medicine (CARPEM), Paris Centre Teaching Hospitals, Paris Descartes University, USPC, Paris, France.
Medical Oncology Department, Cancer Research for Personalized Medicine (CARPEM), Paris Centre Teaching Hospitals, Paris Descartes University, USPC, Paris, France.
Clin Nutr. 2018 Apr;37(2):558-565. doi: 10.1016/j.clnu.2017.01.007. Epub 2017 Jan 19.
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.
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 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).
Abnormal basal energy metabolism identifies patients at higher risk of treatment-related acute complications.
营养和体能状态(PS)的改变与化疗毒性风险增加相关。癌症患者常出现静息能量消耗(REE)增加,这可能导致恶病质。我们研究了异常能量代谢是否可以预测癌症治疗的早期急性限制毒性(ELT)。
在这项观察性单中心研究中,在治疗开始前通过间接热量法测量 REE。根据测量的 REE 与 Harris-Benedict 公式预测的 REE 的比值,患者被分为低代谢组(<90%)、正常代谢组(90-110%)或高代谢组(>110%)。研究了体重指数、体重减轻、PS、白蛋白、转甲状腺素、C 反应蛋白(CRP)和肌肉量(CT 扫描)。任何计划外住院或任何导致治疗第一周期剂量减少或停药的不良事件均定义为 ELT。
我们共纳入 277 例患者:76%为转移性疾病;89%接受化疗,11%接受靶向治疗;29%为正常代谢,51%为高代谢,20%为低代谢。59 例(21%)患者发生 ELT。毒性与异常代谢(与正常相比:OR=2.37[1.13-4.94],p=0.023)、PS(2-3 与 0-1:OR=2.04[1.12-3.74],p=0.023)、白蛋白(<35 与≥35g/l:OR=2.39[1.03-5.54],p=0.048)和炎症(CRP≥10 与<10mg/l:OR=2.43[1.35-4.38],p=0.004)相关。为了预测毒性,最敏感的参数是 REE(83%),其次是 PINI(63%)、GPS(59%)、CRP(55%)、PS(41%)、NRI(37%)和白蛋白(16%)。多变量分析显示,CRP 升高是毒性的独立预测因子(p=0.047)。
基础能量代谢异常可识别出发生治疗相关急性并发症风险较高的患者。