Lee, M.J., Lamidi, S., Williams, K.M. et al. (6 more authors) (2024) Commentary: core descriptor sets using consensus methods support ‘table one’ consistency. Journal of Clinical Epidemiology, 174. 111470. ISSN 0895-4356
Abstract
Background
Inconsistent reporting of patient characteristics in clinical research hampers reproducibility and limits analysis opportunities. This paper proposes condition-specific ‘Core Descriptor Sets’ comprising key factors like demographics, disease severity, comorbidities, and prognosis to standardize Table 1 reporting.
Methods
Development entails stakeholder involvement, systematic identification of descriptors, value rating, and consensus-building using multiple Delphi rounds. Final agreement comes at an expert meeting.
Conclusion
Benefits include easier cross-study comparison, for example, through individual patient meta-analysis, facilitated by comparison of consistently reported individual data rather than group-level analysis. This may also support routine data analyses, subgroup and risk identification, and reduced research waste. Core Descriptor Sets describe cohorts thoroughly while minimizing research burden. They are intended to enable improved clinical characterization, personalization, reproducibility, data sharing, and knowledge building.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2024 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
Keywords: | Consensus; Data Analysis; Documentation; Epidemiologic Research Design; Guidelines as Topic; Prognosis; Publishing; Reproducibility of Results; Research Design; Risk Factors |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Medicine, Dentistry and Health (Sheffield) > School of Medicine and Population Health |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 13 Aug 2024 13:15 |
Last Modified: | 13 Aug 2024 13:15 |
Status: | Published |
Publisher: | Elsevier BV |
Refereed: | Yes |
Identification Number: | 10.1016/j.jclinepi.2024.111470 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:215260 |