ArticleJAMIA open2026
PRIMUS: a precision medicine platform reusing clinical trials and registry data to support treatment selection in multiple sclerosis.
Article in JAMIA open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Authors and funding
18 authors.
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Abstract
Objectives: The "Projections In Multiple Sclerosis" (PRIMUS) project aims to develop a precision medicine platform enabling neurologists to support therapeutic decisions in multiple sclerosis by visualizing similar patient data in a reference database. We present a data integration method to combine randomized clinical trials (RCTs) and observational studies data and optimize the informativeness of the resulting database. Material and Methods: We developed an extract-transform-load data integration pipeline to combine 13 source databases: the "mother" and "high-definition" cohorts from the French MS registry and 11 industrial RCTs (31 786 patients). We aimed to inform each treatment class initiation with at least 500 patients with a 2-year clinical and MRI follow-up. Our data integration strategy used every patient visit as a potential baseline time point to inform a specific neurologist' query to the platform, thus tailoring the actual analysis cohort to each visiting patient. Results: The PRIMUS database had 12 953 patients with at least one informative visit, using the per-visit integration. It could inform treatment initiation scenarios with at least 485 patients for glatiramer acetate and at most 1754 for natalizumab. For instance, our per-visit integration method identified 1306 patients in the high-definition cohort against 610 with the classical epidemiological per-patient integration. Although the mother cohort's longitudinal data were deemed sparse, we identified 6128 informative patients. Discussion: Neurologists would query the PRIMUS database through a web application to support discussions with their patients and the selection of disease-modifying treatments. Conclusion: Our data integration pipeline enabled the creation of a highly informative reference database.
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