Building Bridges from Data to Evidence: Harmonisation Strategies for Real-World Data from Multiple Sclerosis Registries and Cohorts

Abstract

Importance of real-world data (RWD) in multiple sclerosis (MS) research RWD from registries and cohorts is invaluable for understanding MS, a chronic autoimmune disease affecting the central nervous system. It provides insights beyond what clinical trial data can offer, primarily through longitudinal patient observation and follow-up. Challenges in transitioning from RWD to real-world evidence (RWE) MS registries and cohorts aim to capture a comprehensive view of the disease, treatment efficacy and safety, or quality of life while adhering to local requirements and preferences. This variety of requirements and preferences often results in individually defined datasets with varying levels of detail and adherence to local rather than global standards. This data heterogeneity represents one of the main challenges in using MS RWD for RWE generation and collaboration. Harmonisation strategies for MS RWD We developed specific harmonisation strategies to address data heterogeneity, including adopting globally agreed-upon core datasets for MS. We highlighted the definition of a general MS core dataset of 44 variables as a step towards further harmonising MS RWD and facilitating collaboration within the MS community. Expanding collaboration beyond the MS community We investigated the suitability of standardisation initiatives for RWD in healthcare, specifically the Observational Health Data Sciences and Informatics (OHDSI), which utilises the Observational Medical Outcome Partnership (OMOP) common data model (CDM) for MS RWD from registries and cohorts. This exploration formed part of efforts to unlock collaboration opportunities for MS registry and cohort data with other RWD sources, like electronic health records. Feasibility pilot and tool development Within the European Health Data and Evidence Network (EHDEN) project, we conducted a pilot transformation of MS RWD sources to assess feasibility, highlighting challenges in the conversion process. These lessons learned supported the development of “SwitchBox,” a tool designed to automate the conversion of MS RWD in a specific format to the OMOP CDM, making the process more efficient and less resource-intensive.