Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, 02114, USA.
Harvard Medical School, Boston, Massachusetts, 02115, USA.
Ann Clin Transl Neurol. 2023 Oct;10(10):1776-1789. doi: 10.1002/acn3.51866. Epub 2023 Aug 6.
To develop an automated, physiologic metric of immune effector cell-associated neurotoxicity syndrome among patients undergoing chimeric antigen receptor-T cell therapy.
We conducted a retrospective observational cohort study from 2016 to 2020 at two tertiary care centers among patients receiving chimeric antigen receptor-T cell therapy with a CD19 or B-cell maturation antigen ligand. We determined the daily neurotoxicity grade for each patient during EEG monitoring via chart review and extracted clinical variables and outcomes from the electronic health records. Using quantitative EEG features, we developed a machine learning model to detect the presence and severity of neurotoxicity, known as the EEG immune effector cell-associated neurotoxicity syndrome score.
The EEG immune effector cell-associated neurotoxicity syndrome score significantly correlated with the grade of neurotoxicity with a median Spearman's R of 0.69 (95% CI of 0.59-0.77). The mean area under receiving operator curve was greater than 0.85 for each binary discrimination level. The score also showed significant correlations with maximum ferritin (R 0.24, p = 0.008), minimum platelets (R -0.29, p = 0.001), and dexamethasone usage (R 0.42, p < 0.0001). The score significantly correlated with duration of neurotoxicity (R 0.31, p < 0.0001).
The EEG immune effector cell-associated neurotoxicity syndrome score possesses high criterion, construct, and predictive validity, which substantiates its use as a physiologic method to detect the presence and severity of neurotoxicity among patients undergoing chimeric antigen receptor T-cell therapy.
开发一种用于评估嵌合抗原受体-T 细胞治疗患者免疫效应细胞相关神经毒性综合征的自动化生理指标。
我们对 2016 年至 2020 年期间在两家三级保健中心接受嵌合抗原受体-T 细胞治疗（针对 CD19 或 B 细胞成熟抗原配体）的患者进行了回顾性观察队列研究。我们通过图表审查确定了每位患者在脑电图监测期间的每日神经毒性等级，并从电子病历中提取了临床变量和结果。使用定量脑电图特征，我们开发了一种机器学习模型来检测神经毒性的存在和严重程度，称为脑电图免疫效应细胞相关神经毒性综合征评分。
脑电图免疫效应细胞相关神经毒性综合征评分与神经毒性等级具有显著相关性，中位数 Spearman's R 为 0.69（95%置信区间为 0.59-0.77）。对于每个二进制判别水平，平均接收者操作特征曲线下面积均大于 0.85。该评分还与最大转铁蛋白（R 0.24，p=0.008）、最小血小板（R -0.29，p=0.001）和地塞米松的使用量（R 0.42，p<0.0001）显著相关。该评分与神经毒性持续时间显著相关（R 0.31，p<0.0001）。
脑电图免疫效应细胞相关神经毒性综合征评分具有较高的标准、结构和预测效度，这证明了它作为一种生理方法在检测接受嵌合抗原受体 T 细胞治疗的患者神经毒性的存在和严重程度方面的有效性。
