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Introducing a core dataset for real-world data in multiple sclerosis registries and cohorts: Recommendations from a global task force.
Parciak, Tina; Geys, Lotte; Helme, Anne; van der Mei, Ingrid; Hillert, Jan; Schmidt, Hollie; Salter, Amber; Zakaria, Magd; Middleton, Rodden; Stahmann, Alexander; Dobay, Pamela; Hernandez Martinez-Lapiscina, Elena; Iaffaldano, Pietro; Plueschke, Kelly; Rojas, Juan I; Sabidó, Meritxell; Magyari, Melinda; van der Walt, Anneke; Arickx, Francis; Comi, Giancarlo; Peeters, Liesbet M.
Afiliação
  • Parciak T; University MS Center (UMSC), Hasselt-Pelt, Belgium.
  • Geys L; UHasselt, Biomedical Research Institute (BIOMED), Diepenbeek, Belgium.
  • Helme A; UHasselt, Data Science Institute (DSI), Diepenbeek, Belgium.
  • van der Mei I; University MS Center (UMSC), Hasselt-Pelt, Belgium.
  • Hillert J; UHasselt, Biomedical Research Institute (BIOMED), Diepenbeek, Belgium.
  • Schmidt H; UHasselt, Data Science Institute (DSI), Diepenbeek, Belgium.
  • Salter A; Multiple Sclerosis International Federation, London, UK.
  • Zakaria M; Menzies Institute for Medical Research, University of Tasmania, The Australian MS longitudinal study (AMSLS), Hobart, TAS, Australia.
  • Middleton R; Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.
  • Stahmann A; Accelerated Cure Project, iConquerMS People-Powered Research Network, Waltham, MA, USA.
  • Dobay P; Section on Statistical Planning and Analysis, UT Southwestern Medical Center, NARCOMS Registry, COViMS Registry, Dallas, TX, USA.
  • Hernandez Martinez-Lapiscina E; Department of Neurology, Ain Shams University, Cairo, Egypt.
  • Iaffaldano P; Population Data Science, Swansea University Medical School, Swansea, UK.
  • Plueschke K; German MS Register by the German MS Society, MS Research and Project Development gGmbH (MSFP), Hanover, Germany.
  • Rojas JI; Biogen, Baar, Switzerland.
  • Sabidó M; Office of Therapies for Neurological and Psychiatric Disorders (H-NEU), Human Medicines (H-Division), European Medicines Agency, Amsterdam, The Netherlands.
  • Magyari M; Department of Translational Biomedicine and Neurosciences (DiBraiN), Università degli Studi di Bari Aldo Moro, Italian MS registry, Bari, Italy.
  • van der Walt A; Data Analytics and Methods Task Force, European Medicines Agency, Amsterdam, The Netherlands.
  • Arickx F; Neurology Department, Hospital Universitario de CEMIC, RelevarEM, Buenos Aires, Argentina.
  • Comi G; Department of Epidemiology, Merck Healthcare KGaA, Darmstadt, Germany.
  • Peeters LM; Danish Multiple Sclerosis Registry and Danish Multiple Sclerosis Center, Department of Neurology, Copenhagen University Hospital - Rigshospitalet, Glostrup, Denmark.
Mult Scler ; 30(3): 396-418, 2024 Mar.
Article em En | MEDLINE | ID: mdl-38140852
ABSTRACT

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.
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Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Esclerose Múltipla Limite: Humans Idioma: En Revista: Mult Scler Assunto da revista: NEUROLOGIA Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Bélgica

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Esclerose Múltipla Limite: Humans Idioma: En Revista: Mult Scler Assunto da revista: NEUROLOGIA Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Bélgica