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利用ZUMA临床试验数据对未发生早期CRS/NE毒性的复发/难治性大B细胞淋巴瘤患者进行分类。

Classification of patients with relapsed/refractory large B-cell lymphoma who do not develop early CRS/NE toxicity using ZUMA clinical trial data.

作者信息

Speth Kelly, Xie Jin, Song Qinghua, Mattie Mike, Kim Jenny J, Barrett David M, Andrade Jorge, Shen Rhine, Bedognetti Davide, Adhikary Sabina

机构信息

Kite, a Gilead Company, Santa Monica, California, USA.

Kite, a Gilead Company, Santa Monica, California, USA

出版信息

J Immunother Cancer. 2025 Aug 4;13(8):e011819. doi: 10.1136/jitc-2025-011819.

Abstract

BACKGROUND

We aimed to develop an actionable and feasible prospective clinical model to estimate toxicity risk to assist chimeric antigen receptor (CAR) T-cell therapy providers with the management of patients with relapsed and/or refractory large B-cell lymphoma.

METHODS

We conducted an observational, retrospective cohort study using secondary data from 390 patients treated with the CD19 CAR T-cell therapy axicabtagene ciloleucel under two prospective clinical trials, ZUMA-1 and ZUMA-7; these clinical trials enrolled patients with relapsed/refractory large B-cell lymphoma between 2015 and 2019. Using machine learning and statistical methods, we developed a classification model for identifying patients unlikely to experience early cytokine release syndrome (CRS) and neurological events (NE) of any grade.

RESULTS

We found the use of prophylactic corticosteroids to be an important factor in remaining CRS-free and NE-free within the first 3 days post-treatment (p<0.001). We identified a top model for no early CRS/NE using a set of six pre-lymphodepletion clinicopathologic features: number of lines of prior systemic therapy, age, baseline tumor burden (as measured by sum of the product of the diameters), C-reactive protein, aspartate transaminase, and hemoglobin, which achieves a positive predictive value of 0.71 in the holdout validation cohort. Additionally, we find that predicted probabilities generated from the model are strongly associated with incidence of Grade 2 or higher NE.

CONCLUSIONS

We illustrated that routine clinicopathologic variables can be used to identify patients at low risk of developing early post-treatment CRS and/or NE. Such knowledge can be used to help treating centers prospectively manage patient care, including consideration of outpatient treatment.

摘要

背景

我们旨在开发一种可操作且可行的前瞻性临床模型,以评估毒性风险,从而协助嵌合抗原受体(CAR)T细胞疗法的提供者管理复发和/或难治性大B细胞淋巴瘤患者。

方法

我们进行了一项观察性回顾性队列研究,使用了来自两项前瞻性临床试验ZUMA-1和ZUMA-7中接受CD19 CAR T细胞疗法阿基仑赛治疗的390例患者的二次数据;这些临床试验纳入了2015年至2019年间复发/难治性大B细胞淋巴瘤患者。我们使用机器学习和统计方法,开发了一种分类模型,用于识别不太可能发生任何级别的早期细胞因子释放综合征(CRS)和神经事件(NE)的患者。

结果

我们发现使用预防性皮质类固醇是治疗后前3天内无CRS和无NE的重要因素(p<0.001)。我们使用一组六个淋巴细胞清除前临床病理特征确定了一个无早期CRS/NE的顶级模型:既往全身治疗线数、年龄、基线肿瘤负荷(通过直径乘积之和测量)、C反应蛋白、天冬氨酸转氨酶和血红蛋白,该模型在验证队列中的阳性预测值为0.71。此外,我们发现该模型生成的预测概率与2级或更高等级NE的发生率密切相关。

结论

我们证明了常规临床病理变量可用于识别治疗后早期发生CRS和/或NE风险较低的患者。这些知识可用于帮助治疗中心前瞻性地管理患者护理,包括考虑门诊治疗。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c722/12323518/e5986f6c39d2/jitc-13-8-g001.jpg

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