Albert Cid Royo, Roel Elbers Jhj, Daniel Weibel, Vjola Hoxhaj, Zeynep Kurkcuoglu, Miriam C J Sturkenboom, Tiago A Vaz, Constanza L Andaur Navarro
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We designed a machine-readable metadata schema containing study sections, codelists, and time anchoring definitions specified in the SAPs with adaptability and user-friendliness.</p><p><strong>Results: </strong>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).</p><p><strong>Discussion: </strong>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.</p><p><strong>Conclusion: </strong>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.</p>","PeriodicalId":19782,"journal":{"name":"Pharmacoepidemiology and Drug Safety","volume":"33 12","pages":"e70062"},"PeriodicalIF":2.4000,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11602246/pdf/","citationCount":"0","resultStr":"{\"title\":\"Real-World Evidence BRIDGE: A Tool to Connect Protocol With Code Programming.\",\"authors\":\"Albert Cid Royo, Roel Elbers Jhj, Daniel Weibel, Vjola Hoxhaj, Zeynep Kurkcuoglu, Miriam C J Sturkenboom, Tiago A Vaz, Constanza L Andaur Navarro\",\"doi\":\"10.1002/pds.70062\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>To enhance documentation on programming decisions in Real World Evidence (RWE) studies.</p><p><strong>Materials and methods: </strong>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.</p><p><strong>Results: </strong>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).</p><p><strong>Discussion: </strong>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.</p><p><strong>Conclusion: </strong>RWE-BRIDGE offers a systematic approach to detailing variables, time anchoring, and algorithms for RWE studies. 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Real-World Evidence BRIDGE: A Tool to Connect Protocol With Code Programming.
Objective: To enhance documentation on programming decisions in Real World Evidence (RWE) studies.
Materials and methods: 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.
Results: 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).
Discussion: 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.
Conclusion: 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.
期刊介绍：
The aim of Pharmacoepidemiology and Drug Safety is to provide an international forum for the communication and evaluation of data, methods and opinion in the discipline of pharmacoepidemiology. The Journal publishes peer-reviewed reports of original research, invited reviews and a variety of guest editorials and commentaries embracing scientific, medical, statistical, legal and economic aspects of pharmacoepidemiology and post-marketing surveillance of drug safety. Appropriate material in these categories may also be considered for publication as a Brief Report.
Particular areas of interest include:
design, analysis, results, and interpretation of studies looking at the benefit or safety of specific pharmaceuticals, biologics, or medical devices, including studies in pharmacovigilance, postmarketing surveillance, pharmacoeconomics, patient safety, molecular pharmacoepidemiology, or any other study within the broad field of pharmacoepidemiology;
comparative effectiveness research relating to pharmaceuticals, biologics, and medical devices. Comparative effectiveness research is the generation and synthesis of evidence that compares the benefits and harms of alternative methods to prevent, diagnose, treat, and monitor a clinical condition, as these methods are truly used in the real world;
methodologic contributions of relevance to pharmacoepidemiology, whether original contributions, reviews of existing methods, or tutorials for how to apply the methods of pharmacoepidemiology;
assessments of harm versus benefit in drug therapy;
patterns of drug utilization;
relationships between pharmacoepidemiology and the formulation and interpretation of regulatory guidelines;
evaluations of risk management plans and programmes relating to pharmaceuticals, biologics and medical devices.
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