使用自控树基扫描统计的高通量查,以确定与严重急性肝损伤住院相关的药物
Vincent Lo Re1,2, Craig W Newcomb2, Dean M Carbonari2
1Division of Infectious Diseases, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Pharmacoepidemiology and drug safety
|December 5, 2025
概括
这项研究使用了基于树的扫描统计数据和真实世界的数据来识别与严重急性肝损伤 (ALI) 相关的药物. 这些发现突出了潜在的肝毒药物,以便在制药流行病学研究中进一步调查.
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.
- 肝毒性检测检测 肝毒性检测
背景情况:
- 传统的药物诱导性肝损伤的鉴定依赖于病例报告.
- 现实数据的高通量选提供了一种可扩展的方法来检测肝毒性信号.
研究的目的:
- 将基于树的扫描统计数据应用于现实数据,以识别与严重急性肝损伤 (ALI) 住院相关的药物.
- 对没有肝/胆道疾病的患者和患有慢性肝病 (CLD) 的患者进行单独的分析.
主要方法:
- 使用退伍军人卫生管理局数据 (2000-2023) 实施了一种自我控制的病例交叉设计.
- 使用基于条件的伯努利树扫描统计数据来确定潜在的药物-ALI关联 (p < 0.3).
- 对因实验室确认的严重ALI住院的患者进行了分析.
主要成果:
- 在没有肝脏/胆道疾病的患者中,相关药物包括抑制酸的药物 (拉尼蒂丁,奥梅普拉) 和抗emetics (ondansetron).
- 在患有慢性肝病 (CLD) 的患者中,相关药物包括利尿剂 (斯皮罗诺拉克,富洛塞米德),抗emetics,和止痛药 (吗啡, oxycodone, fentanyl).
- 在这两组患者中也发现了特定的抗生素和化疗剂.
结论:
- 高通量查与基于树的扫描统计数据有效检测出潜在的肝毒药物.
- 这些发现需要在药理流行病学研究中进一步调查,以确认药物安全信号.
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