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一种新型营养不良评估模型预测 C 型凝集素样分子-1 CAR-T 细胞治疗后复发/难治性急性髓系白血病的炎症风暴

英文原题:A novel malnutrition assessment model predicts the inflammatory storm of relapsed/refractory acute myeloid leukemia following C-type lectin-like molecule-1 chimeric antigen receptor T therapy.

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A novel malnutrition assessment model predicts the inflammatory storm of relapsed/refractory acute myeloid leukemia following C-type lectin-like molecule-1 chimeric antigen receptor T therapy.

PubMed 2025/07/04(内容时间) Front Nutr Q1 · IF 5.5(JCR 2025)

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研究概要

早期营养不良评估模型是预测接受 CLL1 CAR-T 治疗的复发/难治性 AML 患者炎症风暴的实用、客观工具。

研究思路结论见上方概要

既往研究在解决白血病患者营养不良及免疫治疗输注后炎症风暴方面存在不足。本研究探讨复发/难治性急性髓系白血病(r/r AML)患者中,营养不良与C型凝集素样分子-1CAR-T(CLL1 CAR-T)输注后炎症风暴之间的关系。

在这项单中心研究中,我们采用控制营养状况(CONUT)和改良控制营养状况(mCONUT)来评估患者的营养不良状况。收集不同时间点的CONUT/mCONUT评分以及细胞因子风暴的严重程度和分级。采用受试者工作特征曲线下面积(AUC)评估营养不良评分对CLL1 CAR-T 输注后早期炎症风暴的预测价值。

较高的营养不良评分与细胞因子释放综合征(CRS)严重程度增加显著相关。在CLL1 CAR-T 输注后第+7天和第+14天,营养不良评估模型的预测效能较高,AUC大于0.8,CONUT第+7天达到峰值(AUC = 0.813),CONUT第+14天(AUC = 0.8009)。mCONUT第+7天达到峰值(AUC = 0.821),mCONUT第+14天(AUC = 0.8162)。

展开英文摘要原文

Previous studies have been insufficient in addressing malnutrition in leukemia patients and inflammatory storms following immunotherapy infusion. This study investigates the relationship between malnutrition and inflammatory storm after C-type lectin-like molecule-1 chimeric antigen receptor T (CLL1 CAR-T) infusion in relapsed/refractory acute myeloid leukemia (r/r AML) patients.

In this single-center study, we adopted Controlling Nutritional Status (CONUT) and modified Controlling Nutritional Status (mCONUT) to assess the patient's malnutrition status. The score of CONUT/mCONUT and the severity and grading of cytokine storm at different time points were collected. The area under the receiver operating curve (AUC) was used to evaluate the malnutrition score to predict the early inflammatory storm after CLL1 CAR-T infusion.

Higher malnutrition scores were significantly associated with increased severity of cytokine release storm (CRS). On Day + 7 and Day + 14 after CLL1 CAR-T infusion, the prediction efficiency of the malnutrition assessment model was high, AUC was greater than 0.8, and CONUT Day + 7 reached the peak (AUC = 0.813), and CONUT Day + 14 (AUC = 0.8009). mCONUT Day + 7 reached the peak (AUC = 0.821), and mCONUT Day + 14 (AUC = 0.8162).

Early malnutrition assessment models are practical, objective tools for predicting inflammatory storms in relapsed/refractory AML patients undergoing CLL1 CAR-T therapy.

论文信息

作者
Zhang T、Li M、Zhang X、Zhao M、Jiang Y、Wang X、Zhao Y、Shi X
第一作者单位
Nankai University, Tianjin, China.China
通讯作者单位
Department of Hematology, School of Medicine, Tianjin First Central Hospital, Tianjin Thrombosis and Hemostasis Institute, Nankai University, Tianjin, China.China
期刊
Frontiers in nutrition2025
原文标识
PubMed 40686821 · DOI 10.3389/fnut.2025.1627624