用现实世界的数据来研究动态疾病过程
Richard J Cook1, Jerald F Lawless2, Lily Zou3
1R.J. Cook, PhD, Department of Statistics and Actuarial Science, University of Waterloo, 200 University Avenue West, Waterloo, ON N2L 3G1, Canada.
The Journal of rheumatology
|September 1, 2025
概括
很难从医疗记录中获得关于治疗效果的真实证据. 联合模型可以修复疾病活动影响患者访问和治疗变化的偏差.
科学领域:
- 生物统计学
- 流行病学
- 医疗服务研究
背景情况:
- 来自观察数据的真实世界证据至关重要,但很难获得.
- 医疗保健访问和治疗变化通常与疾病活动相关,引入偏差.
- 与疾病相关的访问和根据指示的治疗可能会扭曲对疾病进展和治疗疗效的理解.
研究的目的:
- 通过观察健康数据获得有效的RWE.
- 为了证明与疾病相关的访问和治疗变化产生的偏见.
- 将联合建模作为克服这些局限性的方法.
主要方法:
- 用于疾病,标志物,治疗和观察 (访问) 过程的联合模型.
- 采用多状态示例模型来模拟偏差.
- 将关节模型应用于牛皮关节炎患者的数据.
主要成果:
- 证明疾病相关因素如何影响观察性研究.
- 展示了联合模型在纠正这些偏见方面的实用性.
- 提供了关于牛皮关节炎治疗效果的见解.
结论:
- 联合模型提供了一个强大的方法来分析复杂的疾病过程中的真实数据.
- 这种方法可以更准确地了解干预效应.
- 准确的RWE对于明智的临床决策和患者护理至关重要.
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