Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden.
Department of Neuroscience, Central Clinical School, Monash University, Melbourne, VIC, Australia.
J Neurol. 2024 Jun;271(6):3616-3624. doi: 10.1007/s00415-024-12303-6. Epub 2024 Apr 1.
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.
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.
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.
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.
大型多发性硬化症数据(BMSD)网络(https://bigmsdata.org)于 2014 年启动,包括捷克共和国、丹麦、法国、意大利和瑞典的国家多发性硬化症(MS)注册中心以及国际 MSBase 注册中心。BMSD 解决了数据共享的伦理、法律、技术和治理相关挑战,迄今为止,已发表了三篇关于汇总数据集的科学论文,作为其协作设计的概念验证。
尽管 BMSD 注册中心在不同的平台上独立运行,但变量、定义和数据结构的相似性允许对数据进行联合分析。在 BMSD 达成共识后,对各注册中心收集不良事件数据的方式进行了某些协调修改,显示出共同发展的能力。
外部赞助商可以通过协调中心提出科学项目,每个注册中心独立决定参与,尊重其治理结构。研究数据集以项目为基础建立,并根据统一的核心数据模型开发项目特定的数据模型。为了克服数据共享的挑战,BMSD 制定了联合数据分析的程序。
目前,BMSD 正在寻求欧洲药品管理局(EMA)的资格意见,以进行授权后安全性研究(PASS),并旨在为授权后有效性研究(PAES)也争取资格意见。BMSD 希望促进 MS 领域真实世界证据研究的发展。