Li Zhaohui, Gu Jun, Du Zhiqiang, Lu Rongrong, Jiang Ying, Zhu Haohao
Affiliated Mental Health Center of Jiangnan University, Wuxi Central Rehabilitation Hospital, Wuxi, Jiangsu 214151, China.
Affiliated Mental Health Center of Jiangnan University, Wuxi Central Rehabilitation Hospital, Wuxi, Jiangsu 214151, China.
J Affect Disord. 2025 Apr 1;374:46-54. doi: 10.1016/j.jad.2025.01.022. Epub 2025 Jan 8.
This study aims to analyze the distribution of adverse events (AEs) related to Lecanemab in real-world settings based on FAERS database data.
Using the FAERS database, AE data related to Lecanemab was collected from Q3 2023 to Q2 2024. Signal mining was conducted using frequency and Bayesian methods to identify positive signals associated with Lecanemab.
A total of 8,284,874 AE reports were collected, with 894 related to Lecanemab. Signal mining identified 22 SOCs, involving 46 PTs. Nervous system disorders had the highest report count, with Amyloid-Related Imaging Abnormalities (ARIA) being the most prominent AE, with high report numbers and signal strength, manifesting as brain edema, microhemorrhages, and iron deposits in the brain. Additionally, infusion-related reactions were common, including headache, chills, and fever. The study also revealed some new potential AEs, such as anger, cognitive disorder, disorientation, and abnormal dreams. Although these psychiatric symptoms had a lower report count, their high signal strength suggests that Lecanemab may impact patients' mental states. Rare but severe AEs, such as encephalitis, pancreatic carcinoma, and subdural hematoma, had low report numbers but high signal strength, highlighting potential risks for these severe events, especially in high-risk patients with relevant medical histories.
This study unveils certain potential risks associated with Lecanemab in real-world applications. Further clinical studies are needed to validate these findings and provide guidance for safe medication practices.
本研究旨在基于FAERS数据库数据，分析在真实世界环境中与lecanemab相关的不良事件（AE）的分布情况。
使用FAERS数据库，收集2023年第三季度至2024年第二季度与lecanemab相关的AE数据。采用频率法和贝叶斯法进行信号挖掘，以识别与lecanemab相关的阳性信号。
共收集到8284874份AE报告，其中894份与lecanemab相关。信号挖掘识别出22个系统器官分类（SOC），涉及46个首选术语（PT）。神经系统疾病的报告数量最多，淀粉样蛋白相关影像学异常（ARIA）是最突出的AE，报告数量和信号强度都很高，表现为脑水肿、微出血和脑内铁沉积。此外，输液相关反应很常见，包括头痛、寒战和发热。该研究还揭示了一些新的潜在AE，如愤怒、认知障碍、定向障碍和异常梦境。尽管这些精神症状的报告数量较少，但其高信号强度表明lecanemab可能会影响患者的精神状态。罕见但严重的AE，如脑炎、胰腺癌和硬膜下血肿，报告数量少但信号强度高，突出了这些严重事件的潜在风险，尤其是在有相关病史的高危患者中。
本研究揭示了lecanemab在实际应用中的某些潜在风险。需要进一步开展临床研究以验证这些发现，并为安全用药实践提供指导。
