ArticleBrain communications2024
Patterns and predictors of multiple sclerosis phenotype transition.
Article in Brain communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Choroid plexus volume in multiple sclerosis: a systematic review and meta-analysis of an emerging imaging biomarker.European journal of medical research · 2025Pooled it
- Predictors of secondary progressive multiple sclerosis in a real word retrospective cohort: the role of clinical factors and disease-modifying therapy patterns.Acta neurologica Belgica · 2026Article
- HerMeS: a registry-based evaluation of the HERCULES criteria for identifying nonrelapsing SPMS.Journal of neurology · 2026Article
- Residual inflammation in the cerebrospinal fluid after short- and long-term natalizumab treatment in relapsing-remitting multiple sclerosis.Frontiers in immunology · 2026Observational
- Tolebrutinib for secondary progressive multiple sclerosis: A summary from the Institute for Clinical and Economic Review's California Technology Assessment Forum.Journal of managed care & specialty pharmacy · 2025Article
- Patterns and predictors of transition between multiple sclerosis phenotypes: A longitudinal analysis.Multiple sclerosis journal - experimental, translational and clinicalArticle
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Authors and funding
20 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Currently, there are limited therapeutic options for patients with non-active secondary progressive multiple sclerosis. Therefore, real-world studies have investigated differences between patients with relapsing-remitting multiple sclerosis, non-active secondary progressive multiple sclerosis and active secondary progressive multiple sclerosis. Here, we explore patterns and predictors of transitioning between these phenotypes. We performed a cohort study using data from The Danish Multiple Sclerosis Registry. We included patients with a relapsing-remitting phenotype, registered changes to secondary progressive multiple sclerosis and subsequent transitions between relapsing and non-relapsing secondary progressive multiple sclerosis, which was defined by the presence of relapses in the previous 2 years. We analysed predictors of transitioning from relapsing-remitting multiple sclerosis to relapsing and non-relapsing secondary progressive multiple sclerosis, as well as between the secondary progressive states using a multi-state Markov model. We included 4413 patients with relapsing-remitting multiple sclerosis. Within a median follow-up of 16.2 years, 962 were diagnosed with secondary progressive multiple sclerosis by their treating physician. Of these, we classified 729 as non-relapsing and 233 as relapsing secondary progressive multiple sclerosis. The risk of transitioning from relapsing-remitting to non-relapsing secondary progressive multiple sclerosis included older age (hazard ratio per increase of 1 year in age: 1.044, 95% confidence interval: 1.035-1.053), male sex (hazard ratio for female: 0.735, 95% confidence interval: 0.619-0.874), fewer relapses (hazard ratio per each additional relapse: 0.863, 95% confidence interval: 0.823-0.906), higher expanded disability status scale (hazard ratio per each additional point: 1.522, 95% confidence interval: 1.458-1.590) and longer time on disease-modifying therapies (hazard ratio per increase of 1 year in treatment, high-efficacy disease-modifying therapy: 1.095, 95% confidence interval: 1.051-1.141; hazard ratio, moderate-efficacy disease-modifying therapy: 1.073, 95% confidence interval: 1.051-1.095). We did not find significant predictors associated with the transition from relapsing secondary progressive multiple sclerosis to non-relapsing secondary progressive multiple sclerosis, whereas older age (hazard ratio per increase of 1 year in age: 0.956, 95% confidence interval: 0.942-0.971) prevented the transition from non-relapsing secondary progressive multiple sclerosis to relapsing secondary progressive multiple sclerosis. Our study suggests that transitioning from relapsing-remitting multiple sclerosis to non-relapsing secondary progressive multiple sclerosis depends on well-known factors affecting diagnosing secondary progressive multiple sclerosis. Further transitions between non-relapsing and relapsing secondary progressive multiple sclerosis are only affected by age. These findings add to the knowledge of non-active secondary progressive multiple sclerosis, a patient group with unmet needs in terms of therapies.
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