摘要
目的:基于大数据挖掘分析奥氮平上市后安全警戒信号,为临床合理用药提供参考。方法:利用美国FDA公共数据开放项目(open FDA)调取FDA不良事件报告系统(FAERS)数据库自2004年1月以来收集的奥氮平药物不良事件(ADE)报告,采用报告比值比法(ROR)检测信号,以其95%置信区间下限(ROR 95%CI_(Lower bound))>1提示有安全警戒信号,比较奥氮平和其他抗精神病药(包括喹硫平、氯氮平、利培酮、帕利哌酮、阿立哌唑、齐拉西酮、氯丙嗪、奋乃静、氟哌啶醇)与警戒信号的比例失衡分析结果,以相对报告比(RRR)最大提示其与该警戒信号最相关。结果:共提取得到的11171211份ADE报告中,以奥氮平为怀疑药物的ADE报告27705份,其中以精神疾病分类的ADE报告数与信号数最多,>1000例的ADE信号有药物毒性、药物无效、药物相互作用、体重增加、嗜睡、自杀死亡、过量和恶性综合征(NMS)。ROR法检测数量排序前100位ADE信号中有83个安全警戒信号,其中16个在奥氮平最新药品说明书中未提及,以NMS风险信号最高(ROR 95%CI_(Lower bound)=58.227)。氯丙嗪(RRR=75.271)、氟哌啶醇(RRR=66.164)与NMS风险相关性均高于奥氮平(RRR=52.375)。结论:利用open FDA平台对奥氮平的安全警戒信号进行检测分析,可有效为其后续药物警戒工作提供参考。
Objective:To analyze the security alert signals of olanzapine after marketing by big data mining,and to provide references for rational clinical drug use.Methods:The adverse drug events(ADE)of olanzapine since Jan,2014 were retrieved based on the U.S.Food and Drug Administration(FDA)Adverse Event Reporting System(FAERS)database utilizing the Open Public Data project of FDA(open FDA).The signals were detected by reporting odds ratio(ROR),and the lower bound of 95%confidence interval(ROR 95%CI_(Lower bound))>1 was regarded as the suggestion of security alert signals.The disproportionality analysis results of alert signals for olanzapine vs.other antipsychotic drugs(including quetiapine,clozapine,risperidone,perphenazine,aripiprazole,ziprasidone,chlorpromazine,perphenazine,and haloperidol)were compared,and the highest relative reporting ratio(RRR)indicated the drug were the most probably related with the alert signal.Results:A total of 11171211 reports were retrieved,among which there were 27705 ADE reports that were suspected to be caused by olanzapine.The number of reports and signals referring to psychiatric disorders were the highest.The ADE signals that were above 1000 cases included toxicity to various agents,drug ineffective,drug interaction,weight increased,somnolence,completed suicide,overdose,and neuroleptic malignant syndrome(NMS).Among the top 100 ADE signals,a total of 83 security alert signals were detected by ROR,among which sixteen alert signals were not mentioned in the latest label of olanzapine,and the NMS showed the highest risk(ROR 95%CI_(Lower bound)=58.227).The risk relevance of chlorpromazine(RRR=75.271)and haloperidol(RRR=66.164)in the case of NMS were both greater than that of olanzapine(RRR=52.375).Conclusion:It can effectively provide reference for future pharmacovigilance work to detect and analyze the security alert signals of olanzapine using open FDA platform.
作者
朱秀清
胡晋卿
邓书华
谭亚倩
王占璋
卢浩扬
倪晓佳
李璐
张明
尚德为
温预关
ZHU Xiu-qing;HU Jin-qing;DENG Shu-hua;TAN Ya-qian;WANG Zhan-zhang;LU Hao-yang;NI Xiao-jia;LI Lu;ZHANG Ming;SHANG De-wei;WEN Yu-guan(Department of Pharmacy,The Affiliated Brain Hospital of Guangzhou Medical University/Guangzhou Huiai Hospital\Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders,Guangzhou 510370,China)
出处
《中国新药杂志》
CAS
CSCD
北大核心
2021年第1期87-93,共7页
Chinese Journal of New Drugs
基金
广东省省级科技计划资助项目(2019B030316001):精神疾病生物样本库的建立及临床应用
广东省自然科学基金资助项目(2018A0303130074)
广州市科技计划项目创新平台建设计划资助项目(201805010009):广州市精神疾病临床转化实验室
广州市医学重点学科资助项目(2017—2019)
广州市卫生健康科技资助项目(20201A011047,20202A011016)。
