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:Can one scoring system fit all? Comparative validation of CAR-HEMATOTOX, ALL-HEMATOTOX, and eIPM for predicting immune effector cell-associated hematotoxicity following CAR-T therapy in hematologic malignancies.
Can one scoring system fit all? Comparative validation of CAR-HEMATOTOX, ALL-HEMATOTOX, and eIPM for predicting immune effector cell-associated hematotoxicity following CAR-T therapy in hematologic malignancies.
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CAR-HT、ALL-HT 和 eIPM 模型在 B-ALL、T-ALL/NHL 和 MM 中一致识别出严重 ICAHT 高风险患者。其中,eIPM 作为一种有前景的通用生存预测工具尤为突出。这些模型提供了有价值的预后信息,可指导支持治疗并为 CAR-T 治疗的治疗计划提供依据。
免疫效应细胞相关血液毒性(ICAHT)以持续性血细胞减少和造血恢复延迟为特征,是CAR-T(CAR-T)细胞治疗后常见的并发症。然而,现有预测模型——用于淋巴瘤的CAR-HEMATOTOX(CAR-HT)、用于B-ALL的急性淋巴细胞白血病-HEMATOTOX(ALL-HT)以及早期ICAHT预测模型(eIPM)——在不同血液系统恶性肿瘤中的适用性仍不确定。
我们前瞻性分析了2022年1月至2025年6月期间接受CAR-T 治疗的119例患者,包括B-ALL(n=62)、T-ALL/非霍奇金淋巴瘤(NHL)(n=25)和多发性骨髓瘤(MM,n=32)。评估了CAR-HT、ALL-HT和eIPM模型预测ICAHT严重程度和生存结局的能力。
3级ICAHT在B-ALL中发生率为32.3%,在T-ALL/NHL中为40.0%,在MM患者中为25.0%,而4级发生率分别为33.9%、20.0%和6.3%。CAR-HT将67.2%的患者归类为高风险,ALL-HT将56.3%的ALL/NHL患者识别为高风险。在两个模型中,高风险组的中性粒细胞减少持续时间均显著长于低风险组(CAR-HT:17.7 vs . 5.3 d,P<0.001;ALL-HT:21.3 vs . 7.7 d,P<0.001)。eIPMpre和eIPMpost均与3-4级ICAHT强烈相关(P<0.001)。重要的是,生存分析显示eIPMpre分层能够区分结局:中+高风险患者的1年总生存期(OS)为65%,而低风险患者为84%(P=0.006),1年无病生存期(DFS)为44% vs . 73%(P<0.001)。eIPMpost也观察到相似的预测准确性。
Immune effector cell-associated hematotoxicity (ICAHT), characterized by prolonged cytopenia and delayed hematopoietic recovery, is a common complication following chimeric antigen receptor T (CAR-T) cell therapy. However, the applicability of existing predictive models, CAR-HEMATOTOX (CAR-HT) for lymphoma, acute lymphoblastic leukemia-HEMATOTOX (ALL-HT) for B-ALL, and the early ICAHT prediction model (eIPM), remains uncertain across different hematologic malignancies.
We prospectively analyzed 119 patients who received CAR-T therapy between January 2022 and June 2025, including B-ALL (n=62), T-ALL/non-Hodgkin's lymphoma (NHL) (n=25), and multiple myeloma (MM, n=32). The CAR-HT, ALL-HT, and eIPM models were evaluated for their ability to predict ICAHT severity and survival outcomes.
Grade 3 ICAHT occurred in 32.3% of B-ALL, 40.0% of T-ALL/NHL, and 25.0% of MM patients, while grade 4 rates were 33.9%, 20.0%, and 6.3%, respectively. CAR-HT classified 67.2% of patients as high-risk, and ALL-HT identified 56.3% of ALL/NHL patients as high-risk. In both models, high-risk groups experienced significantly more prolonged neutropenia than low-risk groups (CAR-HT: 17.7 vs . 5.3 d, P<0.001; ALL-HT: 21.3 vs . 7.7 d, P<0.001). Both eIPMpre and eIPMpost strongly correlated with grade 3-4 ICAHT (P<0.001). Importantly, survival analysis showed that eIPMpre stratification distinguished outcomes: 1-year overall survival (OS) was 65% in medium+high-risk vs . 84% in low-risk patients (P=0.006), and 1-year disease-free survival (DFS) was 44% vs . 73% (P<0.001). Similar predictive accuracy was observed with eIPMpost.
The CAR-HT, ALL-HT, and eIPM models consistently identify patients at high risk for severe ICAHT across B-ALL, T-ALL/NHL, and MM. Among these, the eIPM stands out as a promising universal tool for survival prediction. These models provide valuable prognostic insights that can guide supportive care and inform treatment planning in CAR-T therapy.
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