对糖尿病病患者的临床试验和现实世界的数据进行比较研究
Samu Kurki1, Viivi Halla-Aho2, Manuel Haussmann3
1Bayer Oy, Tuulikuja 2, 02100, Espoo, Finland. samu.kurki@bayer.com.
Scientific reports
|January 19, 2024
概括
从电子健康记录 (EHR) 获得的真实世界数据 (RWD) 与随机对照试验 (RCT) 数据进行比较,发现了显著的差异. 验证对于合并这些数据集至关重要,尤其是在临床研究中建立外部控制臂.
科学领域:
- 临床研究方法论临床研究方法论
- 医疗信息学 医疗信息学
- 医学中的数据科学.
背景情况:
- 来自电子健康记录 (EHR) 的真实世界数据 (RWD) 越来越多地与随机对照试验 (RCT) 一起使用或作为其替代品.
- 在RCT和RWD之间数据生成的差异需要在合并数据集之前仔细验证.
- 了解这些差异对于在临床研究中有效利用RWD至关重要.
研究的目的:
- 为了比较糖尿病病 (DKD) 患者数据的特征,从RCT与来自EHR的相应RWD进行RCT.
- 识别和量化RCT和RWD队列之间的患者人口统计,诊断,药物,实验室值和生命体征的差异.
- 评估合并RCT和RWD的可行性,用于诸如创建外部控制臂之类的应用.
主要方法:
- 对DKD RCT数据集 (5,734名患者) 和来自EHR的RWD数据集 (23,523名患者) 的比较分析.
- 利用可视化,统计比较和集群分析来检查人口统计,诊断,药物,实验室结果和生命体征.
- 评估了数据流行,纵向,完整性和采样密度的差异.
主要成果:
- 在RCT和RWD组之间,在流行率,纵向性,完整性和采样密度方面观察到显著差异.
- 集群分析在每个数据集中确定了不同的患者子组,以及包含RCT和RWD患者的重叠子组.
- 该研究强调了RCT和RWD之间的可概括差异,影响了研究规划和数据集成.
结论:
- 验证对于确认结合RCT和RWD的可行性至关重要,特别是用于构建外部控制臂.
- 通过提供基线信息,填补数据缺口,并使子组分析或患者匹配成为可能,RWD可以丰富RCT数据.
- 需要先进的方法来减轻数据集差异,在将RWD与RCT数据集成时,以进行可靠的临床研究.
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