Ju Yaxin, Qin Xiaohong
Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Yuzhong, Chongqing, China.
Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, Sichuan, China
BMJ Open. 2025 Jul 13;15(7):e095652. doi: 10.1136/bmjopen-2024-095652.
Efgartigimod alfa is an important novel drug for the treatment of myasthenia gravis. However, postmarketing safety data for this drug is limited, underscoring the need for comprehensive safety evaluations in real-world populations.
This study aims to identify adverse event (AE) signals associated with efgartigimod alfa using the Food and Drug Administration Adverse Event Reporting System (FAERS) database, with a focus on evaluating unexpected AEs not previously observed in clinical trials. AE reports with efgartigimod alfa as the primary suspect from the first quarter of 2022 to the fourth quarter of 2023 were extracted.
Signal strength was assessed using Reporting Odds Ratio, Proportional Reporting Ratio, Empirical Bayes Geometric Mean and Bayesian Confidence Propagation Neural Network methods at the Preferred Term level.
A total of 1403 valid cases were retrieved. Urinary tract infection was the most reported AE, while procedural headache demonstrated the strongest signal across all four algorithms. Sepsis, atrial fibrillation and transient ischaemic attack were significant unexpected AEs. The median onset time for AEs was 57.00 days, with cumulative incidence of AEs reaching 37.31% at 30 days and 64.25% at 100 days post-treatment initiation.
Our analysis of real-world data from the FAERS database revealed that most significant AEs were consistent with clinical trials, but some unexpected AEs were additionally identified, warranting further investigation.
艾加莫德α是治疗重症肌无力的一种重要新型药物。然而，该药物的上市后安全性数据有限，这凸显了在真实世界人群中进行全面安全性评估的必要性。
本研究旨在使用美国食品药品监督管理局不良事件报告系统（FAERS）数据库识别与艾加莫德α相关的不良事件（AE）信号，重点评估临床试验中未曾观察到的意外AE。提取了2022年第一季度至2023年第四季度以艾加莫德α为主要怀疑对象的AE报告。
在首选术语级别使用报告比值比、比例报告比值比、经验贝叶斯几何均值和贝叶斯置信传播神经网络方法评估信号强度。
共检索到1403例有效病例。尿路感染是报告最多的AE，而程序性头痛在所有四种算法中显示出最强的信号。脓毒症、心房颤动和短暂性脑缺血发作是显著的意外AE。AE的中位发病时间为57.00天，治疗开始后30天AE的累积发生率达到37.31%，100天达到64.25%。
我们对FAERS数据库真实世界数据的分析表明，大多数显著AE与临床试验一致，但另外还识别出一些意外AE，值得进一步调查。
