基于FAERS数据库的内皮素受体拮抗剂肺炎不良事件的信号挖掘
Signal mining of pneumonia-related adverse events caused by endothelin receptor antagonists based on FAERS database
张从金 1钱青 1钱火连 1许汝福 1王强1
作者信息
- 1. 陆军军医大学第二附属医院药剂科(重庆 400037)
- 折叠
摘要
目的 挖掘和分析内皮素受体拮抗剂发生肺炎相关不良事件(ADE)的信号,为临床安全用药提供参考.方法 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,提取2015第1季度至2023第1季度数据,采用报告比值比、比例报告比、贝叶斯置信传播神经网络和多项泊松收缩器进行挖掘.结果 提取到以内皮素受体拮抗剂为主要怀疑对象的肺炎相关ADE报告7 279份,其中安立生坦3 705份,波生坦1 028份,马昔腾坦2 546份.挖掘到与内皮素受体拮抗剂相关的肺炎ADE有68个,其中安立生坦21个,波生坦25个,马昔腾坦22个.采用ADE信号判定标准,形成信号的ADE共有14种,系统器官分类与累及系统均为感染及侵染类疾病.ADE中以感染性肺炎占比最高(93.61％),造成的死亡结局也最多.结论 真实世界中内皮素受体拮抗剂会发生肺炎相关ADE.女性、高龄和高剂量是发生肺炎ADE的重要因素.这提示医疗人员在使用内皮素受体拮抗剂时,需要根据患者生理状态和药物特点个体化用药,保障用药安全.
Abstract
Objective To explore and analyze the signals of pneumonia-related adverse events(ADEs)caused by endothelin receptor antagonists(ERAs)and provide reference for clinical safe medication.Methods Based on the the U.S.Food and Drug Administration(FDA)adverse event reporting system(FAERS)database,the data from the first quarter of 2015 to the first quarter of 2023 was extracted,and reporting odds ratio,pro-portional reporting ratio,Bayesian confidence propagation neural network and multi-item gamma poisson shrinker were used for mining.Results 7 279 reports of pneumonia-related ADEs with ERAs as the main suspects were extracted,including 3 705 reports of ambrisentan,1 028 reports of bosentan and 2 546 reports of macitentan.There were 68 pneumonia ADEs related to ERAs,including 21 ambrisentan,25 bosentan and 22 macitentan.According to the criteria for judging the signal of ADEs,there were 14 kinds of ADEs that formed signals,and all the systems involved in system organ classification were infections and infectious diseases.Infectious pneumonia accounted for the highest proportion of adverse reactions(93.61％)and caused the most deaths.Conclusion In the real world,ERAs can lead to pneumonia related ADEs.Female,elderly,and high-dose are important factors in the occurrence of pneumonia-related ADEs,which suggests that medical personnel need to individualized use drugs based on the patient's physiological status and drug characteristics when using ERAs to ensure medication safety.
关键词
内皮素受体拮抗剂/美国食品药品监督管理局不良事件报告系统/报告比值比法/综合标准法/信号挖掘/药品不良事件Key words
Endothelin receptor antagonists/FDA adverse event reporting system/Reporting odds ratio/Comprehensive standard method/Signal mining/Adverse drug events引用本文复制引用
基金项目
全国中药特色技术传承人才培训项目(国中医药人教函[2023]96号)
重庆市自然科学基金重点项目(CSTB2023NSCQ-ZDX0012)
出版年
2024
NETL
NSTL
万方数据