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基于FAERS数据库的吡仑帕奈致药品不良事件信号挖掘与分析

Data Mining of Perampanel-Associated New Adverse Drug Events Based on FAERS Database
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摘要 目的:基于美国食品药品监督管理局不良事件报告系统(FAERS)数据库,挖掘、评价新型抗癫痫药吡仑帕奈相关药品不良事件(ADE)风险,以期为临床安全用药提供参考。方法:采用比值失衡法,对FAERS数据库2013年第1季度至2022年第1季度共37个季度的数据进行信号挖掘,对符合风险信号检测标准的吡仑帕奈ADE报告进行提取分析,并与药品说明书对比,挖掘新的ADE并分析其规律。结果:共提取吡仑帕奈相关ADE报告17112份,药品说明书中未标注的报告频次较多、信号较强的ADE主要分布于神经系统疾病、多重耐药性、先天性疾病、抗凝血药药效降低和代谢及营养类疾病。结论:临床使用吡仑帕奈时,应多关注神经系统不良反应,对特殊患者群体需评估患者状态,并探索最佳药物剂量,通过个体化治疗保障患者用药安全。 OBJECTIVE:To explore and evaluate the risk of adverse drug events(ADE)induced by new antiepileptic drug pirampanide based on Food and Drug Administration Adverse Event Reporting System(FAERS)database,so as to provide reference for clinical safe drug use.METHODS:Data of 37 quarters(from the first quarter of 2013 to the first quarter of 2022)in the FAERS database were mined by the ratio imbalance method.ADE reports of pirampanide that met the risk signal detection criteria were extracted and analyzed,and compared with the drug instructions to discover new ADE and analyze its rules.RESULTS:A total of 17112 reports of perampanel-associated ADE were extracted.ADE with high reporting frequency and strong signal,which were not marked in the drug instructions,were mainly distributed in nervous system diseases,multiple drug resistance,congenital diseases,decreased anticoagulant effect and metabolic and nutritional diseases.CONCLUSIONS:More attention should be paid to the adverse drug reactions of nervous system when using pirampanide in clinical practice.For special patients,the status should be evaluated,and the optimal drug dose should be explored to ensure the medication safety of patients through individualized treatment.
作者 陈世祺 陶婧 杭永付 谢诚 朱建国 缪丽燕 CHEN Shiqi;TAO Jing;HANG Yongfu;XIE Cheng;ZHU Jianguo;MIAO Liyan(Dept.of Pharmacy,the First Affiliated Hospital of Soochow University,Jiangsu Suzhou 215006,China)
出处 《中国医院用药评价与分析》 2023年第1期108-111,115,共5页 Evaluation and Analysis of Drug-use in Hospitals of China
基金 国家自然科学基金青年项目(No.81703512)。
关键词 吡仑帕奈 药品不良事件 美国食品药品监督管理局不良事件报告系统 数据挖掘 个体化治疗 Perampanel Adverse drug events FDA Adverse Event Reporting System Data mining Indivi-dualized therapy
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