对137种活性物质的药物坚持决定因素的系统评估,以人口层面的真实世界健康数据为基础
Kerli Mooses1, Marek Oja2, Maria Malk2
1Institute of Computer Science, University of Tartu, Tartu, Estonia. kerli.mooses@ut.ee.
Communications medicine
|March 10, 2026
概括
这项研究引入了个人药物坚持评分 (IMAS),以预测患者在各种疾病中的药物坚持和健康结果. IMAS捕获了一致的药物服用行为,使得个性化干预成为可能.
科学领域:
- 药物经济学和健康研究成果研究成果
- 行为科学与健康 行为科学与健康
- 临床药学和实践 临床药学和实践
背景情况:
- 目前的药物坚持研究仅限于特定的条件,对个人特定的行为影响的了解很少.
- 需要采取全面的方法来评估各种药物和患者行为中的坚持因素.
研究的目的:
- 在137种活性物质中一致评估多种因素对药物坚持的影响.
- 开发和验证个人药物坚持评分 (IMAS) 以预测坚持,其稳定性和健康结果的影响.
主要方法:
- 利用了大量电子健康记录,索赔和发行药物的数据集,对137种活性物质进行了分析.
- 采用连续多次间隔测量药物可用性 (CMA) 和线性混合模型来分析坚持因子.
主要成果:
- 药物依赖性在不同物质之间有显著差异,从0.423的阿尔布特罗尔到0.922的华法林.
- 个人药物坚持评分 (IMAS) 解释了22.0%的坚持变化,优于人口和健康因素 (11.6%).
- IMAS预测了跨药物类别的坚持和降低整体住院风险 (HR=0.76) 和17种疾病的发生率.
结论:
- IMAS是一个强大的个人级别指标,反映了跨治疗类的基线药物服用行为.
- 这个分数有效地预测了药物坚持和相关的健康结果.
- 服用药物的行为是患者一级的一贯现象,支持个性化干预和公共卫生战略.
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