Introducing a core dataset for real-world data in multiple sclerosis registries and cohorts: Recommendations from a global task force

Tina Parciak; Lotte Geys; Anne Helme; Ingrid van der Mei; Jan Hillert; Hollie Schmidt; Amber Salter; Magd Zakaria; Rodden Middleton; Alexander Stahmann; Pamela Dobay; Elena Hernandez Martinez-Lapiscina; Pietro Iaffaldano; Kelly Plueschke; Juan I Rojas; Meritxell Sabidó; Melinda Magyari; Anneke van der Walt; Francis Arickx; Giancarlo Comi; Liesbet M Peeters

doi:10.1177/13524585231216004

Introducing a core dataset for real-world data in multiple sclerosis registries and cohorts: Recommendations from a global task force

Mult Scler. 2024 Mar;30(3):396-418. doi: 10.1177/13524585231216004. Epub 2023 Dec 23.

Authors

Tina Parciak^{1

2

3}, Lotte Geys^{1

2

3}, Anne Helme⁴, Ingrid van der Mei⁵, Jan Hillert⁶, Hollie Schmidt⁷, Amber Salter⁸, Magd Zakaria⁹, Rodden Middleton¹⁰, Alexander Stahmann¹¹, Pamela Dobay¹², Elena Hernandez Martinez-Lapiscina¹³, Pietro Iaffaldano¹⁴, Kelly Plueschke¹⁵, Juan I Rojas¹⁶, Meritxell Sabidó¹⁷, Melinda Magyari¹⁸, Anneke van der Walt¹⁹, Francis Arickx²⁰, Giancarlo Comi²¹, Liesbet M Peeters^{1

2

3}

Affiliations

¹ University MS Center (UMSC), Hasselt-Pelt, Belgium.
² UHasselt, Biomedical Research Institute (BIOMED), Diepenbeek, Belgium.
³ UHasselt, Data Science Institute (DSI), Diepenbeek, Belgium.
⁴ Multiple Sclerosis International Federation, London, UK.
⁵ Menzies Institute for Medical Research, University of Tasmania, The Australian MS longitudinal study (AMSLS), Hobart, TAS, Australia.
⁶ Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.
⁷ Accelerated Cure Project, iConquerMS People-Powered Research Network, Waltham, MA, USA.
⁸ Section on Statistical Planning and Analysis, UT Southwestern Medical Center, NARCOMS Registry, COViMS Registry, Dallas, TX, USA.
⁹ Department of Neurology, Ain Shams University, Cairo, Egypt.
¹⁰ Population Data Science, Swansea University Medical School, Swansea, UK.
¹¹ German MS Register by the German MS Society, MS Research and Project Development gGmbH (MSFP), Hanover, Germany.
¹² Biogen, Baar, Switzerland.
¹³ Office of Therapies for Neurological and Psychiatric Disorders (H-NEU), Human Medicines (H-Division), European Medicines Agency, Amsterdam, The Netherlands.
¹⁴ Department of Translational Biomedicine and Neurosciences (DiBraiN), Università degli Studi di Bari Aldo Moro, Italian MS registry, Bari, Italy.
¹⁵ Data Analytics and Methods Task Force, European Medicines Agency, Amsterdam, The Netherlands.
¹⁶ Neurology Department, Hospital Universitario de CEMIC, RelevarEM, Buenos Aires, Argentina.
¹⁷ Department of Epidemiology, Merck Healthcare KGaA, Darmstadt, Germany.
¹⁸ Danish Multiple Sclerosis Registry and Danish Multiple Sclerosis Center, Department of Neurology, Copenhagen University Hospital - Rigshospitalet, Glostrup, Denmark.
¹⁹ Department of Neuroscience, Central Clinical School, Monash University, Melbourne, VIC, Australia.
²⁰ National Institute for Health and Disability Insurance, Brussels, Belgium.
²¹ Department of Rehabilitation Neurosciences, Casa di Cura Igea, Milan, Italy.

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.

Keywords: Core dataset; database; harmonisation; multiple sclerosis; real-world data; registry.

MeSH terms

Humans
Multiple Sclerosis*
Registries