Evidence map›Paper›PMID 39603653›Full record

ArticlePharmacoepidemiology and drug safety2024

Real-World Evidence BRIDGE: A Tool to Connect Protocol With Code Programming.

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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In one paragraph

Article in Pharmacoepidemiology and drug safety, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Albert Cid RoyoDepartment of Data Science and Biostatistics, Julius Center for Health Science and Primary Care, University Medical Center of Utrecht, Utrecht University, Utrecht, The Netherlands.ORCID 0000-0002-1863-3450
Roel Elbers JhjDepartment of Data Science and Biostatistics, Julius Center for Health Science and Primary Care, University Medical Center of Utrecht, Utrecht University, Utrecht, The Netherlands.
Daniel WeibelDepartment of Data Science and Biostatistics, Julius Center for Health Science and Primary Care, University Medical Center of Utrecht, Utrecht University, Utrecht, The Netherlands.
Vjola HoxhajDepartment of Data Science and Biostatistics, Julius Center for Health Science and Primary Care, University Medical Center of Utrecht, Utrecht University, Utrecht, The Netherlands.
Zeynep KurkcuogluDepartment of Data Science and Biostatistics, Julius Center for Health Science and Primary Care, University Medical Center of Utrecht, Utrecht University, Utrecht, The Netherlands.
Miriam C J SturkenboomDepartment of Data Science and Biostatistics, Julius Center for Health Science and Primary Care, University Medical Center of Utrecht, Utrecht University, Utrecht, The Netherlands.
Tiago A VazDepartment of Data Science and Biostatistics, Julius Center for Health Science and Primary Care, University Medical Center of Utrecht, Utrecht University, Utrecht, The Netherlands.
Constanza L Andaur NavarroDepartment of Data Science and Biostatistics, Julius Center for Health Science and Primary Care, University Medical Center of Utrecht, Utrecht University, Utrecht, The Netherlands.ORCID 0000-0002-7745-2887

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo enhance documentation on programming decisions in Real World Evidence (RWE) studies. MATERIALS AND

methodsWe 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.

resultsWe 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.

conclusionRWE-BRIDGE offers a systematic approach to detailing variables, time anchoring, and algorithms for RWE studies. This metadata schema facilitates communication between researcher and programmers.

Indexed as

Research DesignDatabases, FactualData Interpretation, StatisticalEuropeHumansMetadataSoftwareVaccinesVaccinesdrug safetydrug utilizationelectronic health recordspharmacoepidemiologyvaccines

Identifiers

PMID39603653
PMCPMC11602246

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.