通过代理评估数据质量:我们能否评估欧洲药物局对基于注册表的授权后安全研究数据质量框架的所有维度?
Pamela Dobay1, Meritxell Sabidó2
1Statistical Sciences and Evidence Generation, Biogen International GmbH, Baar, Switzerland.
Pharmacoepidemiology and drug safety
|February 11, 2026
概括
在审批后安全研究 (PASS) 注册表中评估数据质量 (DQ) 的现有工具存在局限性. 我们提出新的数据质量指标 (DQI),以改善营销许可证持有人 (MAHs) 的DQ评估.
科学领域:
- 药物监督 药物监督 药物监督
- 数据科学数据科学数据科学
- 监管科学 监管科学
背景情况:
- 二次数据的使用,特别是基于注册表的研究,对于授权后的监管承诺越来越重要.
- 营销许可证持有人 (MAHs) 经常面临着直接分析患者级数据以进行安全性研究的挑战.
研究的目的:
- 在审批后安全研究 (PASS) 注册表中对数据质量 (DQ) 评估所使用的工具的差异进行映射.
- 描述这些工具的优点和局限性,特别是当直接患者级数据分析受到限制时.
- 提出补充措施,包括数据质量指标 (DQI),以加强DQ评估.
主要方法:
- 与欧洲药物局-DQ框架 (EMA-DQF) 的维度和指标相比,对选定的工具的分析.
- 专注于一个用例,其中DQ评估仅依赖于注册表文档和因数据访问限制而进行的定性审查.
主要成果:
- 没有单一的工具可以全面覆盖所有DQ维度和指标.
- 工具在评估广泛性,语义连贯性和可靠性方面显示出有限的实用性.
- 数据字典对于精度和结构连贯性是有用的,而出版物对DQ评估的实用性是有限的.
结论:
- 提出的一套一致的信息要求和定量DQI可以补充在PASS生命周期中评估DQ的现有工具.
- 如果在PASS协议准备过程中无法评估DQI,则必须承认对研究结果的不确定性和潜在影响.
- 在PASS启动后,由于DQ不足,需要进行注册表更换或删除的场景规划.
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