Real‐World Evidence BRIDGE: A Tool to Connect Protocol With Code Programming
ABSTRACT 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 f...
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| Veröffentlicht in: | Pharmacoepidemiology and drug safety 2024-12, Vol.33 (12), p.e70062-n/a |
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| creator | Royo, Albert Cid Elbers JHJ, Roel Weibel, Daniel Hoxhaj, Vjola Kurkcuoglu, Zeynep Sturkenboom, Miriam C. J. Vaz, Tiago A. Andaur Navarro, Constanza L. |
| description | ABSTRACT
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. |
| doi_str_mv | 10.1002/pds.70062 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_11602246</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>3147192327</sourcerecordid><originalsourceid>FETCH-LOGICAL-p2652-35878a1391c14d4e7bde7cd462a4a75de080b07b1d32dfcfce8f9bcc16eeafcd3</originalsourceid><addsrcrecordid>eNpdkclOwzAURS0EomVY8AMoEhs2AQ-xnbBBUMogIUAM6tJy7Jc2VRKXJAWx4xP4Rr4El5YKWPnp3qOr93wR2iH4gGBMDye2OZAYC7qCugQnSUg4l6uzmbMw5iLpoI2mGWPsvSRaRx2WCMwEZ110cw-6-Hz_GLi6sEH_JbdQGQhO76_OLvpHwUnw6FwRtC7ouaoC0wZ3tWud8dogb0detTCThrUuy7wabqG1TBcNbC_eTfR03n_sXYbXtxdXvZPrcEIFpyHjsYw1YQkxJLIRyNSCNDYSVEdacgs4ximWKbGM2sxkBuIsSY0hAkBnxrJNdDzPnUzTEqyBqq11oSZ1Xur6TTmdq79OlY_U0L0oQgSmNBI-YX-RULvnKTStKvPGQFHoCty0UYwwJhmXEffo3j907KZ15e_zVCRJQhmVntr9vdJyl5-_9sDhHHjNC3hb-gSrWYnKl6i-S1R3Zw_fA_sCfsKPRg</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>3147192327</pqid></control><display><type>article</type><title>Real‐World Evidence BRIDGE: A Tool to Connect Protocol With Code Programming</title><source>MEDLINE</source><source>Wiley Online Library All Journals</source><creator>Royo, Albert Cid ; Elbers JHJ, Roel ; Weibel, Daniel ; Hoxhaj, Vjola ; Kurkcuoglu, Zeynep ; Sturkenboom, Miriam C. J. ; Vaz, Tiago A. ; Andaur Navarro, Constanza L.</creator><creatorcontrib>Royo, Albert Cid ; Elbers JHJ, Roel ; Weibel, Daniel ; Hoxhaj, Vjola ; Kurkcuoglu, Zeynep ; Sturkenboom, Miriam C. J. ; Vaz, Tiago A. ; Andaur Navarro, Constanza L.</creatorcontrib><description>ABSTRACT
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.</description><identifier>ISSN: 1053-8569</identifier><identifier>ISSN: 1099-1557</identifier><identifier>EISSN: 1099-1557</identifier><identifier>DOI: 10.1002/pds.70062</identifier><identifier>PMID: 39603653</identifier><language>eng</language><publisher>Chichester, UK: John Wiley & Sons, Inc</publisher><subject>Adaptability ; Collaboration ; Data Interpretation, Statistical ; Databases, Factual ; drug safety ; drug utilization ; electronic health records ; Europe ; Humans ; Metadata ; Original ; pharmacoepidemiology ; Research Design ; Software ; Statistical analysis ; Statistical models ; vaccines ; Vaccines - administration & dosage</subject><ispartof>Pharmacoepidemiology and drug safety, 2024-12, Vol.33 (12), p.e70062-n/a</ispartof><rights>2024 The Author(s). published by John Wiley & Sons Ltd.</rights><rights>2024 The Author(s). Pharmacoepidemiology and Drug Safety published by John Wiley & Sons Ltd.</rights><rights>2024. This article is published under http://creativecommons.org/licenses/by-nc/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><orcidid>0000-0002-1863-3450 ; 0000-0002-7745-2887</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fpds.70062$$EPDF$$P50$$Gwiley$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fpds.70062$$EHTML$$P50$$Gwiley$$Hfree_for_read</linktohtml><link.rule.ids>230,314,780,784,885,1417,27924,27925,45574,45575</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/39603653$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Royo, Albert Cid</creatorcontrib><creatorcontrib>Elbers JHJ, Roel</creatorcontrib><creatorcontrib>Weibel, Daniel</creatorcontrib><creatorcontrib>Hoxhaj, Vjola</creatorcontrib><creatorcontrib>Kurkcuoglu, Zeynep</creatorcontrib><creatorcontrib>Sturkenboom, Miriam C. J.</creatorcontrib><creatorcontrib>Vaz, Tiago A.</creatorcontrib><creatorcontrib>Andaur Navarro, Constanza L.</creatorcontrib><title>Real‐World Evidence BRIDGE: A Tool to Connect Protocol With Code Programming</title><title>Pharmacoepidemiology and drug safety</title><addtitle>Pharmacoepidemiol Drug Saf</addtitle><description>ABSTRACT
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.</description><subject>Adaptability</subject><subject>Collaboration</subject><subject>Data Interpretation, Statistical</subject><subject>Databases, Factual</subject><subject>drug safety</subject><subject>drug utilization</subject><subject>electronic health records</subject><subject>Europe</subject><subject>Humans</subject><subject>Metadata</subject><subject>Original</subject><subject>pharmacoepidemiology</subject><subject>Research Design</subject><subject>Software</subject><subject>Statistical analysis</subject><subject>Statistical models</subject><subject>vaccines</subject><subject>Vaccines - administration & dosage</subject><issn>1053-8569</issn><issn>1099-1557</issn><issn>1099-1557</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><sourceid>WIN</sourceid><sourceid>EIF</sourceid><recordid>eNpdkclOwzAURS0EomVY8AMoEhs2AQ-xnbBBUMogIUAM6tJy7Jc2VRKXJAWx4xP4Rr4El5YKWPnp3qOr93wR2iH4gGBMDye2OZAYC7qCugQnSUg4l6uzmbMw5iLpoI2mGWPsvSRaRx2WCMwEZ110cw-6-Hz_GLi6sEH_JbdQGQhO76_OLvpHwUnw6FwRtC7ouaoC0wZ3tWud8dogb0detTCThrUuy7wabqG1TBcNbC_eTfR03n_sXYbXtxdXvZPrcEIFpyHjsYw1YQkxJLIRyNSCNDYSVEdacgs4ximWKbGM2sxkBuIsSY0hAkBnxrJNdDzPnUzTEqyBqq11oSZ1Xur6TTmdq79OlY_U0L0oQgSmNBI-YX-RULvnKTStKvPGQFHoCty0UYwwJhmXEffo3j907KZ15e_zVCRJQhmVntr9vdJyl5-_9sDhHHjNC3hb-gSrWYnKl6i-S1R3Zw_fA_sCfsKPRg</recordid><startdate>202412</startdate><enddate>202412</enddate><creator>Royo, Albert Cid</creator><creator>Elbers JHJ, Roel</creator><creator>Weibel, Daniel</creator><creator>Hoxhaj, Vjola</creator><creator>Kurkcuoglu, Zeynep</creator><creator>Sturkenboom, Miriam C. J.</creator><creator>Vaz, Tiago A.</creator><creator>Andaur Navarro, Constanza L.</creator><general>John Wiley & Sons, Inc</general><general>Wiley Subscription Services, Inc</general><scope>24P</scope><scope>WIN</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>7TK</scope><scope>K9.</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-1863-3450</orcidid><orcidid>https://orcid.org/0000-0002-7745-2887</orcidid></search><sort><creationdate>202412</creationdate><title>Real‐World Evidence BRIDGE: A Tool to Connect Protocol With Code Programming</title><author>Royo, Albert Cid ; Elbers JHJ, Roel ; Weibel, Daniel ; Hoxhaj, Vjola ; Kurkcuoglu, Zeynep ; Sturkenboom, Miriam C. J. ; Vaz, Tiago A. ; Andaur Navarro, Constanza L.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-p2652-35878a1391c14d4e7bde7cd462a4a75de080b07b1d32dfcfce8f9bcc16eeafcd3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Adaptability</topic><topic>Collaboration</topic><topic>Data Interpretation, Statistical</topic><topic>Databases, Factual</topic><topic>drug safety</topic><topic>drug utilization</topic><topic>electronic health records</topic><topic>Europe</topic><topic>Humans</topic><topic>Metadata</topic><topic>Original</topic><topic>pharmacoepidemiology</topic><topic>Research Design</topic><topic>Software</topic><topic>Statistical analysis</topic><topic>Statistical models</topic><topic>vaccines</topic><topic>Vaccines - administration & dosage</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Royo, Albert Cid</creatorcontrib><creatorcontrib>Elbers JHJ, Roel</creatorcontrib><creatorcontrib>Weibel, Daniel</creatorcontrib><creatorcontrib>Hoxhaj, Vjola</creatorcontrib><creatorcontrib>Kurkcuoglu, Zeynep</creatorcontrib><creatorcontrib>Sturkenboom, Miriam C. J.</creatorcontrib><creatorcontrib>Vaz, Tiago A.</creatorcontrib><creatorcontrib>Andaur Navarro, Constanza L.</creatorcontrib><collection>Wiley-Blackwell Open Access Titles</collection><collection>Wiley Free Content</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>Neurosciences Abstracts</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Pharmacoepidemiology and drug safety</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Royo, Albert Cid</au><au>Elbers JHJ, Roel</au><au>Weibel, Daniel</au><au>Hoxhaj, Vjola</au><au>Kurkcuoglu, Zeynep</au><au>Sturkenboom, Miriam C. J.</au><au>Vaz, Tiago A.</au><au>Andaur Navarro, Constanza L.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Real‐World Evidence BRIDGE: A Tool to Connect Protocol With Code Programming</atitle><jtitle>Pharmacoepidemiology and drug safety</jtitle><addtitle>Pharmacoepidemiol Drug Saf</addtitle><date>2024-12</date><risdate>2024</risdate><volume>33</volume><issue>12</issue><spage>e70062</spage><epage>n/a</epage><pages>e70062-n/a</pages><issn>1053-8569</issn><issn>1099-1557</issn><eissn>1099-1557</eissn><abstract>ABSTRACT
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.</abstract><cop>Chichester, UK</cop><pub>John Wiley & Sons, Inc</pub><pmid>39603653</pmid><doi>10.1002/pds.70062</doi><tpages>9</tpages><orcidid>https://orcid.org/0000-0002-1863-3450</orcidid><orcidid>https://orcid.org/0000-0002-7745-2887</orcidid><oa>free_for_read</oa></addata></record> |
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| ispartof | Pharmacoepidemiology and drug safety, 2024-12, Vol.33 (12), p.e70062-n/a |
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| source | MEDLINE; Wiley Online Library All Journals |
| subjects | Adaptability Collaboration Data Interpretation, Statistical Databases, Factual drug safety drug utilization electronic health records Europe Humans Metadata Original pharmacoepidemiology Research Design Software Statistical analysis Statistical models vaccines Vaccines - administration & dosage |
| title | Real‐World Evidence BRIDGE: A Tool to Connect Protocol With Code Programming |
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