肿瘤细胞治疗研究
英文原题：Immune Effector Cell-Associated HLH-Like Syndrome (IEC-HS) in CAR-T and TCE-Treated Myeloma and B-Cell Malignancies: Insights from a Pharmacovigilance Study.
共分析23,315份唯一病例安全性报告（ICSRs），识别出378份（1.62%）IEC-HS报告。
CAR-T 细胞疗法（CAR-T）和T细胞衔接抗体（TCE）革新了复发难治性多发性骨髓瘤（RRMM）、非霍奇金淋巴瘤（NHL）和急性淋巴细胞白血病（ALL）的治疗。免疫效应细胞相关噬血细胞性淋巴组织细胞增多症样综合征（IEC-HS）是一种潜在致命的罕见并发症，以血细胞减少、凝血功能障碍、转氨酶升高和高铁蛋白血症为特征。我们旨在利用美国食品药品监督管理局（FDA）不良事件报告系统（FAERS）数据库，分析接受CAR-T和TCE治疗的RRMM和NHL患者中报告的IEC-HS病例、模式及结局。我们使用FAERS数据库和监管活动医学词典（MEDRA）进行了回顾性上市后药物警戒调查。该数据库于2025年3月20日访问，以检查CAR-T：idecabtagene vicleucel（ide-cel）、ciltacabtagene autoleucel（cilta-cel）、axicabtagene ciloleucel（axi-cel）、brexucabtagene autoleucel（brexu-cel）、tisagenlecleucel（tisa-cel）和lisocabtagene maraleucel（liso-cel），以及TCE（teclistamab、elranatamab、talquetamab、mosunetuzumab、glofitamab和epcoritamab）自其在美国FDA获批以来在美国和非美国人群中的不良反应。采用描述性分析来描述报告比例和结局。计算了发生IEC-HS患者的各产品报告死亡率。使用2024年报告的病例计算报告比值比（ROR）和经验贝叶斯几何均值（EBGM），以比较所报告IEC-HS事件的药物。共分析了23,315份唯一病例安全性报告（ICSRs），识别出378份（1.62%）IEC-HS报告。这些患者中报告的死亡率较高（n = 232/378，61.3%）。进行了正式的不比例分析，仅限于2024年的报告以确保当代比较。tisa-cel（ROR 2.20）和cilta-cel（ROR 2.24）均显示出对IEC-HS具有统计学显著的不比例报告信号。相比之下，axi-cel虽然报告的绝对数量最高（n = 114/378），但在该分析中未显示出显著信号（ROR 1.02），表明其高病例量与其高总体报告频率成比例。teclistamab显示HLH报告的可能性显著降低（ROR 0.43）。IEC-HS是一种罕见但可能致命的并发症。我们的不比例分析确定了tisa-cel和cilta-cel的显著报告信号。对于axi-cel等产品观察到的高绝对病例数似乎反映了高使用率而非不比例的风险，强调了在解读自发报告时使用统计信号检测方法的必要性。
Chimeric antigen receptor T-cell therapy (CAR-T) and T-cell engager antibody (TCE) revolutionized relapsed refractory multiple myeloma (RRMM), non-Hodgkin lymphoma (NHL), and acute lymphoblastic leukemia (ALL) treatment. Immune effector cell-associated hemophagocytic lymphohistiocytosis-like syndrome (IEC-HS) is a potentially fatal rare complication characterized by cytopenia, coagulopathy, transaminasemia, and hyperferritinemia. We aim to analyze the IEC-HS reported cases, patterns, and outcomes in RRMM and NHL patients undergoing CAR-T and TCE therapy utilizing the US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) database. We conducted a retrospective postmarketing pharmacovigilance inquiry using the FAERS database and the Medical Dictionary for Regulatory Activities (MEDRA). The database was accessed on March 20, 2025 to examine the adverse effects of CAR-T: idecabtagene vicleucel (ide-cel), ciltacabtagene autoleucel (cilta-cel), axicabtagene ciloleucel (axi-cel), brexucabtagene autoleucel (brexu-cel), tisagenlecleucel (tisa-cel) and lisocabtagene maraleucel (liso-cel), and TCE (teclistamab, elranatamab, talquetamab, mosunetuzumab, glofitamab, and epcoritamab) since their FDA approval in the United States and non-US populations. Descriptive analysis was used to describe reported proportions and outcomes. Reported mortality per product was calculated for patients with IEC-HS. Cases reported in 2024, were used to calculate reporting odds ratio (ROR) and empirical Bayesian geometric mean (EBGM) to compare the drugs for IECHS events reported. A total of 23,315 unique case safety reports (ICSRs) were analyzed, identifying 378 (1.62%) reports of IEC-HS. Reported mortality was high among these patients (n = 232/378, 61.3%). A formal disproportionality analysis, limited to 2024 reports to ensure a contemporary comparison, was performed. Tisa-cel (ROR 2.20) and cilta-cel (ROR 2.24) both demonstrated statistically significant disproportionate reporting signals for IEC-HS. In contrast, axi-cel, which accounted for the highest absolute number of reports (n = 114/378), did not show a significant signal in this analysis (ROR 1.02), suggesting its high case volume is proportional to its high overall reporting frequency. Teclistamab showed a significantly reduced likelihood of HLH reporting (ROR 0.43). IEC-HS is a rare but potentially fatal complication. Our disproportionality analysis identifies significant reporting signals for tisa-cel and cilta-cel. The high absolute number of cases observed for products like axi-cel appears to reflect high utilization rather than a disproportionate risk, underscoring the necessity of using statistical signal detection methods when interpreting spontaneous reports.
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