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CAR-T 治疗后复发/难治性 B 细胞恶性肿瘤患者的病毒感染预测模型:一项回顾性分析

英文原题:A viral infection prediction model for patients with r/r B-cell malignancies after CAR-T therapy: a retrospective analysis.

查看英文原题

A viral infection prediction model for patients with r/r B-cell malignancies after CAR-T therapy: a retrospective analysis.

PubMed 2025/03/21(内容时间) Front Oncol Q2 · IF 3.4(JCR 2025)

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研究概要

我们建立了列线图以预测各因素对 CAR-T 治疗后病毒感染的影响,并发现基线淋巴细胞比例以及早期或近期使用 G-CSF 能够预测 r/r B-ALL 和 B-NHL 患者 CAR-T 治疗后的病毒感染。

中文摘要

CAR-T 细胞治疗后病毒感染可能导致严重并发症。本研究旨在识别复发/难治性B细胞急性淋巴细胞白血病(R/R B-ALL)或B细胞非霍奇金淋巴瘤(B-NHL)患者发生病毒感染的风险因素并建立预测模型。

回顾性纳入45例患者,分析治疗后3个月内病毒感染情况及临床特征。

基线淋巴细胞比例较低与感染风险升高相关,而早期使用粒细胞集落刺激因子(G-CSF)具有保护作用。队列分为训练组(28例)和验证组(17例);模型在两组中的曲线下面积(AUC)分别为0.935和0.869。

该模型可能有助于识别CAR-T 治疗后病毒感染高风险患者,但仍需更大队列验证。

展开英文摘要原文

Chimeric antigen receptor T cell (CAR-T) therapy for relapsed/refractory (r/r) B cell acute lymphoblastic leukemia (B-ALL) and B cell non-Hodgkin lymphoma (B-NHL) patients has shown promising effects, but side effects such as viral infections have been observed.

A total of 45 patients with r/r B-ALL and r/r B-NHL were included in this retrospective study. Patient demographics were recorded, with the primary endpoint being viral infection within 3 months post CAR-T treatment. Univariate and multivariate logistic regression analyses and least absolute shrinkage and selection operator (LASSO) regression analysis were used to analyze independent factors. The patients were divided into a training cohort of 28 and a validation cohort of 17 to construct a prediction model based on determined independent factors. The model's discrimination and calibration were assessed using the receiver operating characteristic curve (ROC), calibration plot, and decision curve analysis (DCA curve).

The univariate and multivariate logistic regression analyses of the 43 patients showed that low baseline lymphocyte ratio was an independent risk factor and using granulocyte colony-stimulating factor (G-CSF) early was a protective factor for viral infection after CAR-T therapy in patients with B-ALL and B-NHL. Based on that, the area under the ROC curve (AUC) of the training cohort and validation cohort was 0.935 (95% CI 0.837-1.000) and 0.869 (95%CI 0.696-1.000), respectively, showing excellent predictive value.

We established a nomogram to predict the factors' influence on viral infection after CAR-T therapy and found that the ratio of baseline lymphocytes and using G-CSF early or lately were able to predict viral infection after CAR-T therapy in r/r B-ALL and B-NHL.

论文信息

作者
Guo S、Liu J、Wang B、Zhang X、Zhao Y、Xu J、Cao X、Zhao M
第一作者单位
First Center Clinical College, Tianjin Medical University, Tianjin, China.China
通讯作者单位
Department of Hematology, Tianjin First Central Hospital, Tianjin, China.China
期刊
Frontiers in oncology2025
原文标识
PubMed 40190552 · DOI 10.3389/fonc.2025.1549809