Are we in a Big Data era for multiple sclerosis? Lessons from integrating clinical trials and observational studies data into the PRIMUS precision medicine platform

ObjectiveThe "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 among a reference database. We present a data integration method to combine randomized clinical trials (RCTs) and observational studies data and optimize their informativeness. MethodsWe developed an extract-transform-load data integration pipeline to combine 13 source databases with 31,786 patients: the "mother" and "high-definition" cohorts from the French MS registry and eleven industrial RCTs. We aimed to inform each treatment class initiation with at least 500 patients with 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 patient. ResultsThe resulting PRIMUS database had 12,953 patients with at least one informative visit. It could inform 7/8 common treatment initiation scenarios with at least 500 patients (range: 485 for glatiramer acetate; 1,754 for natalizumab). The per-visit integration identified 696 more patients in the high-definition cohort than the classical epidemiological per-patient integration (+114 %). Although the mother cohorts longitudinal data were deemed to be sparse, we identified 6,128 informative patients (yield: 27.8%; mean: 2.2 visits per patient). InterpretationA data integration pipeline and per-visit integration enabled us to build a highly informative reference database to be queried by neurologists through a web application to support discussions with their patients and the selection of disease-modifying treatments.