在药监监报告系统中识别怀孕不良药反应:EudraVigilance开发的新型算法
Cosimo Zaccaria1, Loris Piccolo2, María Gordillo-Marañón3
1European Medicines Agency, Domenico Scarlattilaan 6, 1083 HS, Amsterdam, The Netherlands. Cosimo.Zaccaria@ema.europa.eu.
Drug safety
|June 19, 2024
概括
一个新的算法显著提高了EudraVigilance在怀孕期间检测药物不良反应 (ADRs) 的性能,与以前的方法相比,识别了90%的病例. 这增强了对孕妇药物安全性的监测.
科学领域:
- 药物监督 药物监督 药物监督
- 药品安全 药品安全
- 生殖健康 生殖健康
背景情况:
- 极其需要改善关于怀孕期间药物安全性的证据基础.
- 欧德拉警戒 (EudraVigilance,简称EV) 是欧洲经济区的主要系统,用于管理疑似药物不良反应 (ADRs).
- 目前的EV电子提交缺乏怀孕期间药物暴露的特定数据元素,阻碍了安全信号的检测.
研究的目的:
- 在EudraVigilance中开发和验证一种基于规则的新型算法,以更准确地识别怀孕期间的不良反应.
- 解决现有方法的局限性,以区分与其他病例类型的真正与怀孕相关的副作用.
主要方法:
- 一个新的算法被开发和定制,以提高怀孕期间识别疑似ADR的准确性.
- 该算法的性能与标准化MedDRA查询 (SMQ) "怀孕和新生儿主题" (PNT) 相比进行了基准测试.
- 该SMQ PNT被认为可以检索非ADR妊娠相关的结果,因此需要采用精细的方法.
主要成果:
- 这种新的算法表现出卓越的性能,正确识别了90%的与怀孕有关的ADR病例.
- 基准的SMQ PNT在识别这些案例时只达到54%的准确性.
- 在EV中实现算法导致检索了202,426个相关案例.
结论:
- 开发的算法代表了EudraVigilance在怀孕特定药监信号检测方面取得的重大进展.
- 这种精细的怀孕相关的ADR报告的子集为未来关于不成比例方法的研究提供了基础.
- 这项研究提高了监测孕妇药物安全性的能力,为公共卫生做出了贡献.
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