超越处方:慢性药物坚持预测大规模队列研究中的死亡风险
Jessica Hamuy Blanco1, Dina C Janse van Rensburg2, Audrey Jansen van Rensburg2
1Department of Pharmacology, Faculty of Health Sciences, University of Pretoria, Pretoria, South Africa.
Frontiers in pharmacology
|December 11, 2025
概括
药物坚持风险评分 (MARS) 可以识别高死亡风险的个体,特别是与25-55岁的人的年龄相结合时. 这一分数有助于比慢性药物坚持的传统方法更好地分层风险.
科学领域:
- 药物经济学和健康研究成果研究成果
- 流行病学和生物统计学
- 医疗保健服务研究 医疗服务研究
背景情况:
- 药物不服药是一个重要的公共卫生问题,导致死亡率和医疗保健成本增加.
- 现有的风险分层模型可能无法完全捕捉与不坚持慢性药物相关的死亡风险.
- 药物坚持风险评分 (MARS) 使用药房交易数据来评估坚持.
研究的目的:
- 评估药物坚持风险评分 (MARS) 在分层死亡风险方面的有效性.
- 为了确定MARS是否与传统方法相比提高了风险预测,特别是对于患有慢性疾病的人来说.
- 评估MARS类别与死亡结果之间的关系.
主要方法:
- 追溯队列研究分析药店交易数据.
- 在MARS类别的死亡率经验 (实际与预期的比率和相对风险) 与标准的完全承保基础的比较.
- 应用LASSO回归和Cox比例危险模型进行时间对事件分析.
主要成果:
- 整个研究群体的死亡率高于预期的基数 (AER = 175%).
- 当与年龄段 (25-55岁) 相结合时,MARS有效地区分了死亡风险,较高的得分表明AER和RR增加.
- 时间到事件分析显示,MARS类别和生存时间 (p < 0.001) 之间存在统计学上显著的反向关系.
结论:
- 马斯模型,特别是当与年龄相结合时,证明了在特定人群 (25-55岁) 中识别高死亡风险的实用性.
- 传统的风险评估模型可能低估了药物坚持问题较高的人群中的死亡率.
- 在慢性药物管理中,MARS为增强风险分层提供了有价值的工具.
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