Body composition as a predictor of toxicity after treatment with eribulin for advanced soft tissue sarcoma
Body composition as a predictor of toxicity after treatment with eribulin for advanced soft tissue sarcoma
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DOI：
10.1007/s10147-018-1370-8
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发表时间：
2019-04-01
影响因子：
3.3
通讯作者：
Tanaka, Sakae
中科院分区：
文献类型：
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作者：
Kobayashi, Hiroshi;Okuma, Tomotake;Tanaka, Sakae
背景 尽管艾瑞布林对晚期软组织肉瘤（STS）患者的总生存期有临床益处，但治疗相关毒性会降低患者的生活质量。身体成分指标（BCMs）与多种癌症的不良预后及药物毒性相关。本研究旨在探讨BCMs能否预测接受艾瑞布林治疗的晚期STS患者发生药物毒性的情况。
方法 本研究纳入了2016年3月至2018年4月期间接受艾瑞布林治疗的23例晚期STS患者。在开始治疗前或后1个月内通过计算机断层扫描（CT）评估BCMs。评估BCMs与其他临床因素的关系，并使用分类与回归树（CART）分析建立药物毒性风险组的分类模型。
结果 16例患者（69.6%）发生任何3/4级毒性反应。11例患者（47.8%）出现4级血液学毒性，骨骼肌测量值（SMG）低（P = 0.02）和治疗前中性粒细胞计数低（P = 0.0002）的患者中该毒性发生率显著更高。6例患者（26.1%）发生3/4级非血液学毒性，SMG低（P = 0.004）和血清白蛋白水平低（P = 0.02）的患者中该毒性发生率更高。5例高体重指数（BMI）患者（P = 0.03）出现发热性中性粒细胞减少症（FN），且治疗前中性粒细胞计数低（P = 0.02）。CART分析划分出三个风险组，4级血液学不良事件、3/4级非血液学不良事件、FN的受试者工作特征曲线下面积（AUROCC）分别为0.92、0.88、0.92。
结论 SMG是晚期STS患者艾瑞布林药物毒性的重要预测因素。通过结合预测因素对药物毒性进行风险分类，有助于改进化疗中使用的治疗策略。
Background Despite the clinical benefits of eribulin on overall survival of advanced soft tissue sarcoma (STS) patients, treatment-related toxicity reduces their QOL. Body composition metrics (BCMs) are associated with poor outcome and drug toxicities in several cancers. This study investigated whether BCMs could predict drug toxicity occurrence in advanced STS patients treated with eribulin.Methods This study included 23 advanced STS patients treated with eribulin between March 2016 and April 2018. BCMs were evaluated using a CT scan obtained within 1 month before or after treatment initiation. The relationship of BCMs and other clinical factors was evaluated and CART analysis used to develop classification models for risk groups of drug toxicity.Results Sixteen patients (69.6%) experienced any grade 3/4 toxicity. Eleven patients (47.8%) developed G4 hematologic toxicity, which was significantly higher in those with low skeletal muscle gauge (SMG) (P=0.02) and low pretreatment neutrophil count (P=0.0002). Six patients (26.1%) had grade 3/4 non-hematologic toxicity, and was higher in those with low SMG (P=0.004), and low serum albumin level (P=0.02). Five patients with high BMI (P=0.03) experienced febrile neutropenia (FN) and low pretreatment neutrophil count (P=0.02). CART analysis classified three risk groups, and area under the receiver operating characteristic curve (AUROCC) was 0.92, 0.88, 0.92 in G4 hematologic AE, G3/4 non-hematologic AE, FN, respectively.Conclusions SMG is a significant predictive factor of eribulin drug toxicity in advanced STS patients. Risk classification of drug toxicity through combining predictive factors, could improve the therapeutic strategy used in chemotherapy.