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TBDBT: A TB DataBase Template for collection of harmonized TB clinical research data in REDCap, facilitating data standardisation for inter-study comparison and meta-analyses

Authors :
Elsa Du Bruyn
Charlotte Schultz
Jon Ambler
Katherine Johnston
Nicki Tiffin
Angharad G Davis
Amanda Jackson
Taryn Allie
Linda Boloko
Sean Wasserman
Robert J. Wilkinson
Graeme Meintjes
Wellcome Trust
European and Developing Countries Clinical Trial Partnership
European and Developing Countries Clinical Trials Partnership
Source :
PLoS ONE, Vol 16, Iss 3, p e0249165 (2021), PLoS ONE
Publication Year :
2021
Publisher :
Public Library of Science (PLoS), 2021.

Abstract

Clinical tuberculosis research, both within research groups and across research ecosystems, is often undertaken in isolation using bespoke data collection platforms and applying differing data conventions. This failure to harmonise clinical phenotype data or apply standardised data collection and storage standards in turn limits the opportunity to undertake meta-analyses using data generated across multiple research projects for the same research domain. We have developed the Tuberculosis DataBase Template (TBDBT), a template for the well-supported, free and commonly deployed clinical databasing platform, REDCap. This template can be used to set up a new tuberculosis research database with a built-in set of standardised data conventions, to ensure standardised data capture across research projects and programs. A modular design enables researchers to implement only the modules of the database template that are appropriate for their particular study. The template includes core modules for informed consent data, participant demographics, clinical symptoms and presentation, diagnostic imaging and laboratory tests. Optional modules have been designed for visit scheduling and calendar functionality, clinical trial randomisation, study logistics and operations, and pharmacokinetic data. Additional fields can be added as needed. This REDCap template can facilitate collection of high-quality data for tuberculosis research, providing a tool to ensure better data harmonisation, analysis and meta-analysis.

Details

Language :
English
ISSN :
19326203
Volume :
16
Issue :
3
Database :
OpenAIRE
Journal :
PLoS ONE
Accession number :
edsair.doi.dedup.....03078555b79623b7d8a6e8f84fc0cb9d