Mining and analysis of adverse drug event signals related to macitentan

WU Zhenhu; CHEN Xinyao; CHEN Yaoxin; XU Yinji

doi:10.6039/j.issn.1001-0408.2024.13.15

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Mining and analysis of adverse drug event signals related to macitentan

更新时间：2024-07-10

- Mining and analysis of adverse drug event signals related to macitentan
- ZHONGGUO YAOFANG Vol. 35, Issue 13, Pages: 1628-1633(2024)
- 作者机构：
  
  1.广东省中医院呼吸与危重症医学科，广州　510120
  2.广州中医药大学第二临床医学院，广州　510405
  3.中山大学公共卫生学院，广州　510080
- 作者简介：
- 基金信息：
- DOI：10.6039/j.issn.1001-0408.2024.13.15
  CLC： R969.3;R972
- Published：15 July 2024，
  
  Received：28 November 2023，
  
  Revised：27 April 2024，
- 稿件说明：
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吴镇湖,陈鑫遥,陈耀鑫等.马昔腾坦相关不良事件信号的挖掘与分析 ^Δ[J].中国药房,2024,35(13):1628-1633.

WU Zhenhu,CHEN Xinyao,CHEN Yaoxin,et al.Mining and analysis of adverse drug event signals related to macitentan[J].ZHONGGUO YAOFANG,2024,35(13):1628-1633.
吴镇湖,陈鑫遥,陈耀鑫等.马昔腾坦相关不良事件信号的挖掘与分析 ^Δ[J].中国药房,2024,35(13):1628-1633. DOI： 10.6039/j.issn.1001-0408.2024.13.15.

WU Zhenhu,CHEN Xinyao,CHEN Yaoxin,et al.Mining and analysis of adverse drug event signals related to macitentan[J].ZHONGGUO YAOFANG,2024,35(13):1628-1633. DOI： 10.6039/j.issn.1001-0408.2024.13.15.

摘要

目的

挖掘肺动脉高压（PAH）治疗药物马昔腾坦的相关不良事件（ADE）信号，为临床安全用药提供参考。

方法

收集美国FDA不良事件报告系统（FAERS）数据库中2013年第4季度至2023年第3季度的马昔腾坦相关ADE报告，采用比例失衡法中的报告比值比（ROR）法、英国药品和保健品管理局的综合标准法（简称“MHRA法”）进行数据挖掘，根据《国际医学用语词典》26.0版中的系统器官分类（SOC）和首选术语（PT）对ADE名称进行规范化编码，并进行事件发生时间（TTO）分析和威布尔分布形状参数（WSP）检验。

结果

共提取到以马昔腾坦为首要怀疑药物的ADE报告26 079份，涉及患者以女性居多（73.25%），且集中于18～65岁（42.39%），主要上报国家为美国（84.42%），严重治疗结果以住院或住院时间延长（59.82%）最为常见。挖掘出马昔腾坦ADE阳性信号269个；甲状腺功能减退症，血肌酐升高、血尿素升高等肾损伤相关ADE，以及精神淡漠、绝望感等精神障碍相关ADE未被其药品说明书收录。TTO分析结果提示，大部分马昔腾坦ADE阳性信号发生在初始治疗后的0～30 d（492份，21.52%）和＞360 d（411份，17.98%）；WSP检验结果显示，报告数排前20位的ADE阳性信号大多符合早期失败型曲线特征。

结论

临床在应用马昔腾坦治疗PAH时，除药品说明书中提及的不良反应外，还应重点关注甲状腺功能障碍、肾功能障碍、精神障碍等相关ADE。

Abstract

OBJECTIVE

To mine adverse drug event （ADE） signals related to the pulmonary arterial hypertension （PAH） therapeutic drug macitentan， and to provide reference for safe clinical medication.

METHODS

Macitentan-related ADE reports were collected from the US FDA Adverse Event Reporting System （FAERS） database from the fourth quarter of 2013 to the third quarter of 2023. Data mining was conducted by using the reporting odds ratio （ROR）

method

and the comprehensive standard method established by the UK Medicines and Healthcare Products Regulatory Agency （referred to as “MHRA method”） under the proportional imbalance approach. According to the systemic organ class （SOC） and preferred term （PT） stated in 26.0 edition of

Medical Dictionary of Regulatory Activities

， standardized coding of ADE names was performed， followed by the analysis of time to onset （TTO） and the Weibull shape parameter （WSP） test.

RESULTS

Overall， a total of 26 079 ADE reports were identified with macitentan as the primary suspect drug. These reports predominantly involved female patients （73.25%） and were concentrated in the age range of 18 to 65 years （42.39%）. The majority of reports originated from the US （84.42%）， with hospitalization or prolonged hospital stays （59.82%） being the most common in severe treatment outcome. A total of 269 ADE positive signals related to macitentan were identified. Among these， hypothyroidism， ADE related to renal injury such as the increase of serum creatinine and blood urea nitrogen， and ADE related to psychiatric disorders like apathy and despair were not included in the drug label. TTO analysis indicated that the majority of macitentan-related ADE signals occurred between 0-30 days after initial treatment （492 reports， 21.52%） and over 360 days （411 reports， 17.98%）. The results of WSP test showed that most of the top 20 reported ADE signals conformed to the characteristics of an early failure curve.

CONCLUSIONS

When clinically using macitentan in patients with PAH， attention should be given not only to the adverse reactions mentioned on the drug label but also to thyroid dysfunction， kidney dysfunction and mental disorder-related ADEs.

关键词

马昔腾坦肺动脉高压药品不良事件信号挖掘比例失衡法合理用药

Keywords

pulmonary arterial hypertensionadverse drug eventsignal miningproportional imbalance methodrational drug use

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