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The ability to better predict disease progression represents a major unmet need in multiple sclerosis (MS), and would help to inform therapeutic and management choices.

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Modelling disease progression in relapsing–remitting onset multiple sclerosis using multilevel models applied to longitudinal data from two natural history cohorts and one treated cohort