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Big Multiple Sclerosis Data network: an international registry research network.
- Source :
-
Journal of neurology [J Neurol] 2024 Jun; Vol. 271 (6), pp. 3616-3624. Date of Electronic Publication: 2024 Apr 01. - Publication Year :
- 2024
-
Abstract
- Background: The Big Multiple Sclerosis Data (BMSD) network ( https://bigmsdata.org ) was initiated in 2014 and includes the national multiple sclerosis (MS) registries of the Czech Republic, Denmark, France, Italy, and Sweden as well as the international MSBase registry. BMSD has addressed the ethical, legal, technical, and governance-related challenges for data sharing and so far, published three scientific papers on pooled datasets as proof of concept for its collaborative design.<br />Data Collection: Although BMSD registries operate independently on different platforms, similarities in variables, definitions and data structure allow joint analysis of data. Certain coordinated modifications in how the registries collect adverse event data have been implemented after BMSD consensus decisions, showing the ability to develop together.<br />Data Management: Scientific projects can be proposed by external sponsors via the coordinating centre and each registry decides independently on participation, respecting its governance structure. Research datasets are established in a project-to-project fashion and a project-specific data model is developed, based on a unifying core data model. To overcome challenges in data sharing, BMSD has developed procedures for federated data analysis.<br />Future Perspectives: Presently, BMSD is seeking a qualification opinion from the European Medicines Agency (EMA) to conduct post-authorization safety studies (PASS) and aims to pursue a qualification opinion also for post-authorization effectiveness studies (PAES). BMSD aspires to promote the advancement of real-world evidence research in the MS field.<br /> (© 2024. The Author(s).)
Details
- Language :
- English
- ISSN :
- 1432-1459
- Volume :
- 271
- Issue :
- 6
- Database :
- MEDLINE
- Journal :
- Journal of neurology
- Publication Type :
- Academic Journal
- Accession number :
- 38561543
- Full Text :
- https://doi.org/10.1007/s00415-024-12303-6