Commentary: core descriptor sets using consensus methods support 'table one' consistency

doi:10.1016/j.jclinepi.2024.111470

2024-10-01

DOI：10.1016/j.jclinepi.2024.111470

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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. (c) 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.

Keyword:

Consensus

Prognosis

Research design

Risk factors

Data analysis

Documentation

Epidemiologic research design

Guidelines as topic

Pub- lishing

Reproducibility of results

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Journal of Clinical Epidemiology

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University of Birmingham

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