目的 基于美国食品药品管理局不良事件报告系统（FAERS）数据库挖掘伊普可泮不良事件信号，以期为临床安全用药提供参考。方法 下载FAERS数据库2023年第4季度—2025年第3季度的不良事件报告，使用报告比值比（ROR）和贝叶斯可信传播神经网络法（BCPNN）对主要怀疑药品为伊普可泮的不良事件报告进行信号检测，并使用韦伯分布检验评估不良事件的发生规律。结果 共检索到以伊普可泮为首要怀疑药物的不良事件报告396份，其中结局严重的报告占比35.1%。共涉及23个系统器官分类（SOC），剔除药品适应证、疾病临床表现及与药品不良事件无关的信号后，共挖掘到阳性信号28个，其中5个信号未在说明书收录，包括脑雾、口咽疼痛、耳部感染、眼充血和黑便。韦伯分布表明不良事件主要发生在用药后的早期，尤其第1个月，占比44.6%。结论 患者治疗期间除关注伊普可泮常见的不良事件外，应做好对新的不良事件的监测工作，尤其在接受治疗的第1个月。

Objective To mine the adverse event signals of iptacopan based on the FAERS database, aiming to provide references for clinically safe medication. Methods Adverse event reports from the FAERS database (Q4 2023 to Q3 2025) were downloaded. Signal detection was performed on reports in which iptacopan was the primary suspected drug, using the ROR and BCPNN methods. The Weibull distribution test was used to evaluate the onset time of adverse events. Results A total of 396 adverse event reports with iptacopan as the primary suspected drug were retrieved, of which 35.1% had serious outcomes, involving 23 SOCs. After excluding signals related to drug indications, disease clinical manifestations, and unrelated adverse events, 28 positive signals were identified. Among these, five signals were not included in the drug label, including brain fog, oropharyngeal pain, ear infection, eye redness, and melena. The Weibull distribution showed that adverse events mainly occurred in the early stage after drug administration, particularly within the first month, accounting for 44.6%. Conclusion During patient treatment, in addition to monitoring common adverse events of iptacopan, attention should be paid to the monitoring of new adverse events, especially within the first month of treatment.

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