The RECLAIM study aims to gather a centralized and harmonized dataset, enabling the secondary use of data for building AI-based models that will support diagnosis and prognosis of individual Multiple Sclerosis patient's disease course and treatment response in a real-world setting. Additionally, the data will be used to generate further insights on Multiple Sclerosis progression as well as to develop the tools to monitor this progression.
Patients must have a confirmed diagnosis of MS, NMOSD, MOGAD, CIS or RIS.
Patient (or patient's legal representative) has previously signed and dated an informed consent form (ICF) for the secondary use of their data, or assent form. Alternatively, the secondary use of the patient's data is allowed following Institutional Review Board (IRB)/Ethical Committee (EC) approval in accordance with national and local subject privacy regulations.
Patients under 18 years of age will be excluded.
Other unspecified reasons that, in the opinion of the Investigator or Joint Steering Committee, make the patient unsuitable for participation in the study.
The study will include patients with a confirmed diagnosis of MS (Thompson et al., 2018), CIS, RIS, NMOSD (Wingerchuck et al., 2015), or MOGAD (Banwell et al., 2023). No other specifications are included. We envision a database that captures the diversity and heterogeneity of the population, in order to address factors influencing disease worsening that have not been investigated yet or have only been investigated to a very limited extent in previous studies.
Other
Retrospective
Not listed
The number of patients from each institution who have contributed data to the database.
The number of patients from each institution whose data was mapped to the common data model of the harmonised database.
The number of patients from the control arms of clinical trials who have contributed data to the database.
The data completeness of each variable in the harmonised database.
The representativeness of the harmonised dataset for the MS patient population as evaluated by age range, gender balance, the distribution of country of residence, the distribution of race/ethnicity and the distribution of educational level
The validity of the data through an assessment of the amount of erroneous or impossible data entries for each variable.
The temporal uniformity of each institution's data over time as assessed by the number of changes to variables over time (addition of new variables or variables no longer being captured, alterations to how variables are captured).
The temporal uniformity of the harmonised dataset over time as assessed by the average time between subsequent assessments of each variable.
Click on the lead sponsor to view all of their trials.
icometrix
Lead sponsor
Charite University, Berlin, Germany
Collaborator
Ruhr University of Bochum
Collaborator
Technische Universität Dresden
Collaborator
University Hospital, Lille
Collaborator
Casa di Cura IGEA
Collaborator
General University Hospital, Prague
Collaborator
Hoffmann-La Roche
Collaborator
Bristol-Myers Squibb
Collaborator
Imcyse SA
Collaborator
AB Science
Collaborator
Nocturne UG
Collaborator
Aalto University
Collaborator
