Liesbet M Peeters
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Articles (1)
Background: As of September 2022, there was no globally recommended set of core data elements for use in multiple sclerosis (MS) healthcare and research. As a result, data harmonisation across observational data sources and scientific collaboration is limited. Objectives: To define and agree upon a core dataset for real-world data (RWD) in MS from observational registries and cohorts. Methods: A three-phase process approach was conducted combining a landscaping exercise with dedicated discussions within a global multi-stakeholder task force consisting of 20 experts in the field of MS and its RWD to define the Core Dataset. Results: A core dataset for MS consisting of 44 variables in eight categories was translated into a data dictionary that has been published and disseminated for emerging and existing registries and cohorts to use. Categories include variables on demographics and comorbidities (patient-specific data), disease history, disease status, relapses, magnetic resonance imaging (MRI) and treatment data (disease-specific data). Conclusion: The MS Data Alliance Core Dataset guides emerging registries in their dataset definitions and speeds up and supports harmonisation across registries and initiatives. The straight-forward, time-efficient process using a dedicated global multi-stakeholder task force has proven to be effective to define a concise core dataset.
Year:
2023
Collaborators (2)
Melinda Magyari
Associate professor
University of Copenhagen
Rodden Middleton
Associate Professor of Disease Registers and Health Data
Swansea University
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