在FDA不良事件报告系统 (FAERS) 数据库中对乙酸的真实数据分析
Bin Zhao1, Xiaohong Zhang2, Moliang Chen1
1Xiamen Health and Medical Big Data Center (Xiamen Medicine Research Institute), Xiamen, Fujian, China.
这项研究分析了美国食品和药物管理局的数据,以确定与阿司匹林相关的意想不到的不良药物反应 (ADR),揭示了潜在的新安全信号,如白和依赖.
科学领域:
- 药物监督 药物监督 药物监督
- 现实世界的数据分析分析.
- 药物安全 药物安全
背景情况:
- 乙盐酸 (阿司匹林) 是一种广泛使用的药物,有报道的不良事件 (AE).
- 了解阿司匹林的不良药物反应 (ADR) 对患者的安全至关重要.
- 现实世界的数据提供了超越临床试验的药物安全性的见解.
研究的目的:
- 调查阿司匹林潜在的新和意想不到的副作用.
- 用美国食品和药物管理局的不良事件报告系统 (FAERS) 数据库来检测ADR信号.
- 通过不成比例分析来识别阿司匹林的安全信号.
主要方法:
- 对FAERS数据库的回顾性分析.
- 不成比例指标的计算:报告概率比率 (ROR),比例报告比率 (PRR),贝叶斯信任传播神经网络 (BCPNN) 和马-鱼缩小器 (GPS).
- 在各个器官系统中确定与阿司匹林相关的首选术语 (PT).
主要成果:
- 18,644个与阿司匹林相关的AE报告从超过750万个FAERS记录中确定.
- 在25个器官系统中检测到493个与阿司匹林相关的PT.
- 发现的重大意想不到的副作用包括色,依赖性和隔间综合征.
结论:
- 这些发现表明阿司匹林可能会产生新的和意想不到的ADR信号.
- 需要临床验证来确认这些观察到的关联.
- 这项研究为药物不良事件研究提供了一种新的方法.
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