Patterns and predictors of multiple sclerosis phenotype transition

• DOI: 10.1093/braincomms/fcae422
• Publication Date: 2024-11-23T00:00:41Z
• Authors: Luigi Pontieri; Nupur Greene; Malthe Faurschou ...; Svend Sparre Geer...; Nasrin Asgari; Henrik Boye Jensen; Zsolt Illes; Jakob Schäfer; Rikke Marie Jensen; Tobias Sejbæk; Arkadiusz Weglewski; Mie Reith Mahler; Mai Bang Poulsen; Sivagini Prakash; Morten Stilund; Matthias Kant; Peter Vestergaard...; Kristina Bacher S...; Finn Sellebjerg; Melinda Magyari
• Keywords: Clinical phenotype

Abstract Currently, there are limited therapeutic options for patients with non-active secondary progressive multiple sclerosis. Therefore, real-world studies have investigated differences between relapsing-remitting sclerosis, sclerosis and active Here, we explore patterns predictors of transitioning these phenotypes. We performed a cohort study using data from The Danish Multiple Sclerosis Registry. included phenotype, registered changes to subsequent transitions relapsing non-relapsing which was defined by the presence relapses in previous 2 years. analysed as well states multi-state Markov model. 4413 Within median follow-up 16.2 years, 962 were diagnosed their treating physician. Of these, classified 729 233 risk older age (hazard ratio per increase 1 year age: 1.044, 95% confidence interval: 1.035–1.053), male sex female: 0.735, 0.619–0.874), fewer each additional relapse: 0.863, 0.823–0.906), higher expanded disability status scale point: 1.522, 1.458–1.590) longer time on disease-modifying therapies treatment, high-efficacy therapy: 1.095, 1.051–1.141; hazard ratio, moderate-efficacy 1.073, 1.051–1.095). did not find significant associated transition whereas 0.956, 0.942–0.971) prevented Our suggests that depends well-known factors affecting diagnosing Further only affected age. These findings add knowledge patient group unmet needs terms therapies.