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

Autor: Lee MJ; Institute for Applied Health Research, University of Birmingham, Birmingham, UK. Electronic address: m.j.lee.1@bham.ac.uk., Lamidi S; Department of Cardiovascular Sciences, University of Leicester, Leicester, UK., Williams KM; Barnsley Hospital, Barnsley NHS Foundation Trust, Barnsley, UK., Blackwell S; Institute for Applied Health Research, University of Birmingham, Birmingham, UK., Rashid A; Clinical Effectiveness Unit, Royal College of Surgeons of England, London, UK., Coe PO; Department of Upper Gastrointestinal Surgery, Leeds Teaching Hospitals, Leeds, UK., Fearnhead NS; Department of Surgery, Addenbrookes Hospital, Cambridge, UK., Blencowe NS; Centre for Surgical Research, Population Health Sciences, Bristol Medical School, Bristol, UK; Department of Emergency General Surgery, Leeds Teaching Hospitals, Leeds, UK., Hind D; Clinical Trials Research Unit, Section of Health and Related Research, University of Sheffield, Sheffield, UK.
Jazyk: angličtina
Zdroj: Journal of clinical epidemiology [J Clin Epidemiol] 2024 Oct; Vol. 174, pp. 111470. Date of Electronic Publication: 2024 Jul 20.
DOI: 10.1016/j.jclinepi.2024.111470
Abstrakt: 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.
Competing Interests: Declaration of competing interest None to declare.
(Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)
Databáze: MEDLINE
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