Article(id=1322180271772910303, tenantId=1146029695717560320, journalId=1235980733773295621, issueId=1322180233244038010, articleNumber=null, orderNo=null, doi=null, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=null, receivedDateStr=null, revisedDate=null, revisedDateStr=null, acceptedDate=1612281600000, acceptedDateStr=2021-02-03, onlineDate=1793161941711, onlineDateStr=2026-10-28, pubDate=1631635200000, pubDateStr=2021-09-15, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793161941711, onlineIssueDateStr=2026-10-28, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793161941711, creator=13701087609, updateTime=1793161941711, updator=13701087609, issue=Issue{id=1322180233244038010, tenantId=1146029695717560320, journalId=1235980733773295621, year='2021', volume='30', issue='17', pageStart='1537', pageEnd='1632', issueExtLink='null', onlineDate='null', pubDate='1631635200000', pubDateStr='2021-09-15', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1793161932525, creator='13701087609', updateTime=1793162118166, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1322181011941732619, tenantId=1146029695717560320, journalId=1235980733773295621, issueId=1322180233244038010, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1322181011945926924, tenantId=1146029695717560320, journalId=1235980733773295621, issueId=1322180233244038010, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=1627, endPage=1632, ext={EN=ArticleExt(id=1322180271928099552, articleId=1322180271772910303, tenantId=1146029695717560320, journalId=1235980733773295621, language=EN, title=Mining and evaluation of security alert signals of evolocumab based on FAERS, columnId=null, journalTitle=Chinese Journal of New Drugs, columnName=null, runingTitle=null, highlight=null, articleAbstract=
Objective: To explore the security alert signals of evolocumab after marketing using data mining technology in order to provide the basis for safe drug use in clinical.
Methods: FDA Adverse Event Reporting System (FAERS) were searched for 19 quarters since the drug was approved for marketing (3rd quarter of 2015) by the FDA to the 1st quarter of 2020. The measure of disproportionality included the reporting odds ratio and the proportional reporting ratio, the correlation degree of the adverse drug event (ADE) signals was simultaneously calculated.
Results: After multiple screenings, the signals obtained by ROR and PRR completely overlapped in a total of 46 cases, of which 28 adverse event specifications were not appear in the specification. The strong signals of evolocumab were mainly concentrated in myalgia, injection site reaction, and back pain, etc. The largest number of system organ classification (SOC) signals were mainly concentrated in musculoskeletal and connective tissue disorders, infection and infectious diseases, and perception dysfunction, etc. At the same time, it has been discovered that the drug may cause nerve perception dysfunction and increased blood glucose, etc. Through further analysis of the adverse events related to gender and age differences, a total of 14 high-risk signals with gender differences were found. Male patients should be alert to increased blood creatine phosphokinase, and hypoacusis, etc; female patients should be alert to nervousness and swelling face, etc. There were 15 high risk signals with age differences. Non-elderly patients should be alert to increased blood creatine phosphokinase, and increased hepatic enzyme, etc; elderly patients should be alert to hypoacusis, and arthritis, etc.
Conclusion: The signal mining of adverse events through FAERS can deeply analyze the safety of evolocumab after it enters marketed, and then effectively reduce the risk of clinical medication.
, authors=Qi-ying CHEN
1, Tian-yu CHEN
2, Yi-min LI
1, authorsList=Qi-ying CHEN, Tian-yu CHEN, Yi-min LI, authorCompany=null, correspAuthors=Yi-min LI, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1322180272225895137, articleId=1322180271772910303, tenantId=1146029695717560320, journalId=1235980733773295621, language=CN, title=基于FAERS对依洛尤单抗安全警戒信号的挖掘与评价, columnId=1236331163573342670, journalTitle=中国新药杂志, columnName=药物安全与合理应用, runingTitle=null, highlight=null, articleAbstract=
目的： 运用数据挖掘技术探讨依洛尤单抗上市后的安全警戒信号，为临床安全用药提供依据。
方法： 调取美国FDA不良事件报告系统（FAERS），检索时限自该药获得FDA批准上市（2015年第3季度）到2020年第1季度共19个季度，采用比例失衡法中的报告比值比法（ROR）和比例报告比值法（PRR）同时进行ADE信号关联度的计算。
结果： 经过多重筛查，ROR与PRR获得的信号完全重叠，合计46个，其中有28个不良事件说明书未收录。依洛尤单抗较强的信号主要集中在肌痛、注射部位反应、背痛等。系统器官分类（SOC）信号个数最多的主要集中在肌肉骨骼和结缔组织疾病、感染和传染性疾病及神经系统疾病等。同时也挖掘出该药可能引起神经感知功能障碍、血糖升高等。通过对性别、年龄差异的相关不良事件进一步分析，发现有性别差异的高危信号共14个，男性患者应警惕血肌酐磷酸激酶升高、听觉迟钝等；女性患者应警惕紧张、脸肿胀等。有年龄差异的高危信号共15个，非老年患者应警惕血肌酐磷酸激酶升高、肝酶升高等；老年患者应警惕听觉迟钝、关节炎等。
结论： 通过FAERS进行警戒信号的挖掘可较深入地分析依洛尤单抗上市后的安全性，进而有效地降低临床用药风险。
, authors=陈琪莹
1, 陈添玉
2, 李毅敏
1, authorsList=陈琪莹, 陈添玉, 李毅敏, authorCompany=null, correspAuthors=李毅敏, authorNote=
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