CAR-T(CAR-T)细胞疗法在非肿瘤性疾病中的应用
Chimeric antigen receptor T (CAR-T) cell therapy in non-oncological diseases.
CAR-T(CAR-T)细胞在血液系统恶性肿瘤中的应用推动了这种免疫治疗形式的显著进展。
CELL INTELLIGENCE · 肿瘤细胞治疗研究
肿瘤细胞治疗研究
英文原题:Derivation and validation of a novel score for early prediction of severe CRS after CAR-T therapy in haematological malignancy patients: A multi-centre study.
Derivation and validation of a novel score for early prediction of severe CRS after CAR-T therapy in haematological malignancy patients: A multi-centre study.
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CAR-T(CAR-T)细胞疗法可有效诱导血液系统恶性肿瘤完全缓解。重度细胞因子释放综合征(CRS)是该疗法最重要且危及生命的不良反应。本多中心研究在中国 6 家医院开展。训练队列包括 87 例多发性骨髓瘤(MM)患者;外部验证队列分别包括 59 例 MM 患者,以及 68 例急性淋巴细胞白血病(ALL)或非霍奇金淋巴瘤(NHL)患者。研究使用 CAR-T 输注后第 1–2 天的 45 种细胞因子水平及患者临床特征构建列线图。列线图包含 CX3CL1、GZMB、IL4、IL6 和 PDGFAA。基于训练队列,该列线图预测重度 CRS 的偏倚校正 AUC 为 0.876(95% CI:0.871–0.882)。两个外部验证队列的 AUC 均稳定(MM:AUC=0.907,95% CI:0.899–0.916;ALL/NHL:AUC=0.908,95% CI:0.903–0.913)。所有队列的表观及偏倚校准图均与理想线重合。
我们开发的列线图可在患者病情危重前预测重度 CRS 风险,增进对 CRS 生物学的理解,并可能指导未来细胞因子靶向疗法。
Chimeric antigen receptor T (CAR-T) cell therapy is highly effective in inducing complete remission in haematological malignancies. Severe cytokine release syndrome (CRS) is the most significant and life-threatening adverse effect of this therapy. This multi-centre study was conducted at six hospitals in China. The training cohort included 87 patients with multiple myeloma (MM), an external validation cohort of 59 patients with MM and another external validation cohort of 68 patients with acute lymphoblastic leukaemia (ALL) or non-Hodgkin lymphoma (NHL).
The levels of 45 cytokines on days 1-2 after CAR-T cell infusion and clinical characteristics of patients were used to develop the nomogram. A nomogram was developed, including CX3CL1, GZMB, IL4, IL6 and PDGFAA. Based on the training cohort, the nomogram had a bias-corrected AUC of 0.
876 (95% CI = 0. 871-0. 882) for predicting severe CRS. The AUC was stable in both external validation cohorts (MM, AUC = 0. 907, 95% CI = 0. 899-0. 916; ALL/NHL, AUC = 0. 908, 95% CI = 0. 903-0. 913). The calibration plots (apparent and bias-corrected) overlapped with the ideal line in all cohorts.
We developed a nomogram that can predict which patients are likely to develop severe CRS before they become critically ill, improving our understanding of CRS biology, and may guide future cytokine-directed therapies.
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