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Multiple sclerosis (MS) is a chronic demyelinating disease of the central nervous system for which the investigators now have many treatment alternatives. These treatments have a preventive goal and the data in the literature suggest the interest in rapidly achieving optimal control of the disease in order to decrease the risk of long-term disability progression.
One of the current unmet needs is to have markers that can be used at the individual level to predict the long-term prognosis in order to propose optimal and personalized therapeutic management.
Classically used clinical markers do not meet this need. It is recognized that there is a so-called silent course of MS (not measurable by clinical parameters), which may, after several months or years, be expressed as a physical or cognitive disability.
MRI is the reference examination for monitoring the sub-clinical activity of the disease but it does not allow the neurodegenerative side of the disease to be assessed. Other blood or imaging markers are being studied but are not yet usable in daily practice.
The project aims to evaluate the interest in using digital biomarkers, based on a rapid assessment of patients using a locally developed mobile application (MS Screen Test - MSST) to predict the evolutionary prognosis of the disease.
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MIKAEL COHEN
Data sourced from clinicaltrials.gov
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