Department of Data Science and Biostatistics, Julius Center for Health Science and Primary Care, University Medical Center of Utrecht, Utrecht University, Utrecht, The Netherlands.
Pharmacoepidemiol Drug Saf. 2024 Dec;33(12):e70062. doi: 10.1002/pds.70062.
To enhance documentation on programming decisions in Real World Evidence (RWE) studies.
We analyzed several statistical analysis plans (SAP) within the Vaccine Monitoring Collaboration for Europe (VAC4EU) to identify study design sections and specifications for programming RWE studies. We designed a machine-readable metadata schema containing study sections, codelists, and time anchoring definitions specified in the SAPs with adaptability and user-friendliness.
We developed the RWE-BRIDGE, a metadata schema in form of relational database divided into four study design sections with 12 tables: Study Variable Definition (two tables), Cohort Definition (two tables), Post-Exposure Outcome Analysis (one table), and Data Retrieval (seven tables). We provide a guide to populate this metadata schema and a Shiny app that checks the tables. RWE-BRIDGE is available on GitHub (github.com/UMC-Utrecht-RWE/RWE-BRIDGE).
The RWE-BRIDGE has been designed to support the translation of study design sections from statistical analysis plans into analytical pipelines and to adhere to the FAIR principles, facilitating collaboration and transparency between researcher and programmers. This metadata schema strategy is flexible as it can support different common data models and programming languages, and it is adaptable to the specific needs of each SAP by adding further tables or fields, if necessary. Modified versions of the RWE-BRIGE have been applied in several RWE studies within VAC4EU.
RWE-BRIDGE offers a systematic approach to detailing variables, time anchoring, and algorithms for RWE studies. This metadata schema facilitates communication between researcher and programmers.
增强真实世界证据 (RWE) 研究中编程决策的文档记录。
我们分析了欧洲疫苗监测合作组织 (VAC4EU) 中的几个统计分析计划 (SAP)，以确定研究设计部分和用于编程 RWE 研究的规范。我们设计了一个机器可读的元数据架构，其中包含 SAP 中指定的研究部分、代码列表和时间锚定定义，具有适应性和用户友好性。
我们开发了 RWE-BRIDGE，这是一个以关系数据库形式呈现的元数据架构，分为四个研究设计部分，共 12 个表：研究变量定义 (两个表)、队列定义 (两个表)、暴露后结局分析 (一个表) 和数据检索 (七个表)。我们提供了一个填充此元数据架构的指南和一个检查表格的 Shiny 应用程序。RWE-BRIDGE 可在 GitHub (github.com/UMC-Utrecht-RWE/RWE-BRIDGE) 上获得。
RWE-BRIDGE 旨在支持将研究设计部分从统计分析计划转化为分析管道，并遵守 FAIR 原则，促进研究人员和编程人员之间的合作和透明度。这种元数据架构策略具有灵活性，因为它可以支持不同的常见数据模型和编程语言，并且可以通过添加更多的表或字段来适应每个 SAP 的特定需求。在 VAC4EU 中的几个 RWE 研究中应用了修改后的 RWE-BRIDGE 版本。
RWE-BRIDGE 为详细说明 RWE 研究中的变量、时间锚定和算法提供了一种系统的方法。该元数据架构促进了研究人员和编程人员之间的沟通。
