ArticleJournal of neurology2024
Evaluation of drivers of treatment switch in relapsing multiple sclerosis: a study from the Italian MS Registry.
Article in Journal of neurology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 4 citations in OpenAlex.
- Real‑world pharmacovigilance of rituximab‑associated adverse reactions in children and adolescents: Disproportionality signal detection and time‑to‑onset pattern characterization using the FAERS database.Human vaccines & immunotherapeutics · 2026Article
- Big data in multiple sclerosis.Current opinion in neurology · 2026Review
- Exit strategy patterns in second-line therapies for relapsing forms of multiple sclerosis.Acta neurologica Belgica · 2026Article
- Building Towards Initiation, Moderation, De-Escalation and Cessation of Disease-Modifying Treatments for Multiple Sclerosis in Greece: An Expert Panel Consensus Meeting.Brain sciences · 2026Article
- Refining predictors of long-term NEDA-3 status in relapsing-remitting multiple sclerosis: insights from real-world data.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2026Article
- Predictors of therapy switching to high-efficacy disease-modifying therapies in patients with multiple sclerosis: a single center, retrospective, observational study.Frontiers in neurology · 2025Article
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Authors and funding
69 authors at 20 institutions in 1 country.
Funding
Abstract
backgroundActive relapsing-remitting (RR) and secondary progressive (SP) multiple sclerosis (MS) are currently defined as "relapsing MS" (RMS). The aim of this cross-sectional study was to assess drivers of treatment switches due to clinical relapses in a population of RMS patients collected in the Italian MS and Related Disorders Register (I-MS&RD).
methodsRRMS and SPMS patients with at least one relapse in a time window of 2 years before of data extraction were defined as RMS. Factors associated with disease-modifying therapy (DMT) switching due to clinical activity were assessed through multivariable logistic regression models in which treatment exposure was included as the last recorded DMT and the last DMT's class [moderate-efficacy (ME), high-efficacy (HE) DMTs and anti-CD20 drugs].
resultsA cohort of 4739 RMS patients (4161 RRMS, 578 SPMS) was extracted from the I-MS&RD. A total of 2694 patients switching DMTs due to relapses were identified. Switchers were significantly (p < 0.0001) younger, less disabled, more frequently affected by an RR disease course in comparison to non-switcher patients. The multivariable logistic regression models showed that Alemtuzumab (OR 0.08, 95% CI 0.02-0.37), Natalizumab (0.48, 0.30-0.76), Ocrelizumab (0.1, 0.02-0.45) and Rituximab (0.23, 0.06-0.82) exposure was a protective factor against treatment switch due to relapses. Moreover, the use of HE DMTs (0.43, 0.31-0.59), especially anti-CD20 drugs (0.14, 0.05-0.37), resulted to be a protective factor against treatment switch due to relapses in comparison with ME DMTs.
conclusionsMore than 50% of RMS switched therapy due to disease activity. HE DMTs, especially anti-CD20 drugs, significantly reduce the risk of treatment switch.
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