临床药理学
安全药理学
鉴定(生物学)
风险分析(工程)
药物反应
安全监测
药物警戒
计算机科学
患者安全
药物不良反应
统计分析
医学
数据科学
不利影响
药品
药理学
医疗保健
生物信息学
政治学
数学
法学
统计
生物
植物
作者
June S. Almenoff,Edward N. Pattishall,T Gibbs,William DuMouchel,Stephen Evans,Nancy Yuen
标识
DOI:10.1038/sj.clpt.6100258
摘要
Robust tools for monitoring the safety of marketed therapeutic products are of paramount importance to public health. In recent years, innovative statistical approaches have been developed to screen large post-marketing safety databases for adverse events (AEs) that occur with disproportionate frequency. These methods, known variously as quantitative signal detection, disproportionality analysis, or safety data mining, facilitate the identification of new safety issues or possible harmful effects of a product. In this article, we describe the statistical concepts behind these methods, as well as their practical application to monitoring the safety of pharmaceutical products using spontaneous AE reports. We also provide examples of how these tools can be used to identify novel drug interactions and demographic risk factors for adverse drug reactions. Challenges, controversies, and frontiers for future research are discussed. Clinical Pharmacology & Therapeutics (2007) 82 157–166; doi:10.1038/sj.clpt.6100258; published online 30 May 2007
科研通智能强力驱动
Strongly Powered by AbleSci AI