Article(id=1236696515964629032, tenantId=1146029695717560320, journalId=1235980733773295621, issueId=1236696515473895464, 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=1649606400000, acceptedDateStr=2022-04-11, onlineDate=1772781026116, onlineDateStr=2026-03-06, pubDate=1673712000000, pubDateStr=2023-01-15, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1772781026116, onlineIssueDateStr=2026-03-06, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1772781026116, creator=13701087609, updateTime=1772781026116, updator=13701087609, issue=Issue{id=1236696515473895464, tenantId=1146029695717560320, journalId=1235980733773295621, year='2023', volume='32', issue='1', pageStart='1', pageEnd='109', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1772781025999, creator=13701087609, updateTime=1772782685740, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1236703476982542786, tenantId=1146029695717560320, journalId=1235980733773295621, issueId=1236696515473895464, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1236703476982542787, tenantId=1146029695717560320, journalId=1235980733773295621, issueId=1236696515473895464, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=103, endPage=109, ext={EN=ArticleExt(id=1236696516161761322, articleId=1236696515964629032, tenantId=1146029695717560320, journalId=1235980733773295621, language=EN, title=Mining and analysis of security alert signals of neratinib based on FAERS, columnId=null, journalTitle=Chinese Journal of New Drugs, columnName=null, runingTitle=null, highlight=null, articleAbstract=

Objective: To mine the security alert signals of neratinib based on the FDA Adverse Event Reporting System (FAERS) database to provide a reference for the safety of clinical medication. Methods: The adverse drug event (ADE) signals data of neratinib from the FAERS database from the third quarter of 2017 to the third quarter of 2021 were collected. The data mining was performed using the reporting odds ratio (ROR) and the proportional reporting ratio (PRR) in the proportional imbalance method. Results: A total of 1 362 ADE reports with neratinib as the primary suspected drug were collected, and 96 neratinib ADE signals were mined; 71 signals were obtained after excluding non-adverse drug reaction signals, involving 13 systems. Among them, a total of 48 new signals were not mentioned in the instructions, accumulating 12 systems. Gastrointestinal disorders ADE entries totaled 2 186 cases, generating 25 signals; new signals from investigations accounted for 85.71% of their total system signals. Daily dose was not an independent risk factor for the occurrence of gastrointestinal disorders and investigations ADE. Logistic regression results showed that a course of treatment ≤7 days was an independent risk factor for the occurrence of gastrointestinal disorders, with statistically significant results (P=0.008); compared to a course of treatment ≤7 days, a course of treatment 1 to 3 months was an independent risk factor for the occurrence of investigations ADE (OR=4.288, 95% CI of 1.342 to 13.703;P=0.014). Conclusion: No matter what daily dose is used, adverse reactions need to be paid attention to. The duration of medication is of great significance to the risk of adverse reactions of neratinib, and pharmaceutical care should be strengthened during clinical medication.

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目的：基于美国FDA不良事件报告系统（FAERS）数据库挖掘奈拉替尼的安全警戒信号，为临床安全用药提供参考。方法：收集FAERS数据库2017年第3季度至2021年第3季度的奈拉替尼不良事件数据，利用比例失衡法中的报告比值比（ROR）法和比例报告比值比（PRR）法进行数据挖掘。结果：共收集到奈拉替尼为首要怀疑药物的不良事件报告1 362份，挖掘出奈拉替尼不良事件信号96个；排除非药品不良反应信号后得到信号71个，累及13个系统。其中说明书中未提及的新信号共48个，累积12个系统。胃肠道系统不良事件共2 186例，产生25个信号；实验室检查的新信号占其系统信号总数的85.71%。日剂量并非胃肠道系统和实验室检查不良反应发生的独立危险因素。Logistic回归结果显示，疗程≤7 d是发生胃肠道反应的独立危险因素，结果具有统计学意义（P=0.008）；相对于疗程≤7 d，疗程1~3个月是发生实验室检查不良事件的独立危险因素OR=4.288，95%CI为1.342~13.703（P=0.014）。结论：无论以何日剂量用药都需要关注不良反应，用药疗程对奈拉替尼不良反应发生风险存在重要意义，临床使用时应加强药学监护。

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王慧冰，女，硕士，主管药师，主要从事临床药学和医院药学研究。联系电话：(010)66947565，E-mail: shining618@126.com。

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王慧冰，女，硕士，主管药师，主要从事临床药学和医院药学研究。联系电话：(010)66947565，E-mail: shining618@126.com。

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