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Early non-disabling relapses are important predictors of disability accumulation in people with relapsing-remitting multiple sclerosis

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Published:1st Jun 2023
Author: Daruwalla C, Shaygannejad V, Ozakbas S, Havrdova EK, Horakova D, Alroughani R et al.
Availability: Free full text
Ref.:Mult Scler. 2023 Jun;29(7):875-883.
DOI:10.1177/13524585231151951
Early non-disabling relapses are important predictors of disability accumulation in people with relapsing-remitting multiple sclerosis


Background:
The prognostic significance of non-disabling relapses in people with relapsing-remitting multiple sclerosis (RRMS) is unclear.

Objective: To determine whether early non-disabling relapses predict disability accumulation in RRMS.

Methods: We redefined mild relapses in MSBase as 'non-disabling', and moderate or severe relapses as 'disabling'. We used mixed-effects Cox models to compare 90-day confirmed disability accumulation events in people with exclusively non-disabling relapses within 2 years of RRMS diagnosis to those with no early relapses; and any early disabling relapses. Analyses were stratified by disease-modifying therapy (DMT) efficacy during follow-up.

Results: People who experienced non-disabling relapses within 2 years of RRMS diagnosis accumulated more disability than those with no early relapses if they were untreated (n = 285 vs 4717; hazard ratio (HR) = 1.29, 95% confidence interval (CI) = 1.00-1.68) or given platform DMTs (n = 1074 vs 7262; HR = 1.33, 95% CI = 1.15-1.54), but not if given high-efficacy DMTs (n = 572 vs 3534; HR = 0.90, 95% CI = 0.71-1.13) during follow-up. Differences in disability accumulation between those with early non-disabling relapses and those with early disabling relapses were not confirmed statistically.

Conclusion: This study suggests that early non-disabling relapses are associated with a higher risk of disability accumulation than no early relapses in RRMS. This risk may be mitigated by high-efficacy DMTs. Therefore, non-disabling relapses should be considered when making treatment decisions.


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