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Gerstmann-Sträussler-Scheinker syndrome is a rare autosomal dominant disease caused by a mutation in the prion gene, usually manifesting as progressive ataxia with late cognitive decline. A 44-year-old woman with a positive family history developed early personality and behavior changes, followed by paresthesias and ataxia, later associated with memory problems, pyramidal signs, anosognosia and very late myoclonus, spasticity, and severe dysexecutive impairment. Magnetic resonance showed caudate, mesio-frontal, and insular hyper-intensities, electroencephalography revealed generalized triphasic periodic complexes. A pathogenic P102L mutation in the prion gene was detected. Our case differed from classical Gerstmann-Sträussler-Scheinker syndrome by rapid progression, severe dementia, abnormal electroencephalography and magnetic resonance findings, which were highly suggestive of familial Creutzfeldt-Jakob disease. [ABSTRACT FROM AUTHOR]

Background and Objectives: Women with multiple sclerosis (MS) are at risk of disease reactivation in the early postpartum period. Ocrelizumab (OCR) is an anti-CD20 therapy highly effective at reducing MS disease activity. Data remain limited regarding use of disease-modifying therapies (DMTs), including OCR, and disease activity during peripregnancy periods., Methods: We performed a retrospective cohort study using data from the MSBase Registry including pregnancies conceived after December 31, 2010, from women aged 18 years and older, with relapsing-remitting MS or clinically isolated syndrome. Women were classified by preconception exposure to DMTs, including OCR, rituximab (RTX), natalizumab (NAT), stratified into active (NAT-A; continued ≥28 weeks of gestation, restarted ≤1 month postpartum) or conservative (NAT-C; continued ≤4 weeks of gestation, restarted >1 month postpartum) strategies, dimethyl fumarate (DMF) or low-efficacy DMTs (interferon-beta, glatiramer acetate). Annualized relapse rates (ARRs) were calculated for 12-month prepregnancy, pregnancy, and 6-month postpartum periods., Results: A total of 2,009 live births from 1,744 women were analyzed, including 73 live births from 69 women treated with preconception OCR. For OCR, no within-pregnancy relapse was observed and 3 women (4.1%) experienced 1 relapse in the postpartum period (ARR 0.09 [95% CI 0.02-0.27]). For NAT-A, 3 (3.7%) of 82 women relapsed during pregnancy (0.05 [0.01-0.15]) and 4 (4.9%) relapsed during postpartum (0.10 [0.03-0.26]). However, for NAT-C, 13 (15.9%) of 82 women relapsed within pregnancy (0.32 [0.20-0.51]) and 25 (30.5%) relapsed during postpartum (0.74 [0.50-1.06]). In the low-efficacy DMT group, 101 (7.6%) of 1,329 women experienced within-pregnancy relapse (0.12 [0.10-0.14]), followed by an increase in postpartum relapse activity with 234 women (17.6%) relapsing (0.43 [0.38-0.48]). This was similarly seen in the DMF group with 13 (7.9%) of 164 women experiencing within-pregnancy relapse (0.12 [0.06-0.20]) and 25 (15.2%) of 164 relapsing postpartum (0.39 [0.26-0.57]). Our RTX cohort had 0 of 24 women experiencing within-pregnancy relapse and 3 (12.5%) of 24 experiencing postpartum relapse., Discussion: Women treated with OCR or NAT-A were observed to have low relapse rates during pregnancy and postpartum. NAT-C was associated with increased risk of relapses. There was no within-pregnancy relapse in our RTX cohort, although we caution overinterpretation due to our sample size. An effective DMT strategy with a favorable safety profile for the mother and infant should be discussed and implemented well in advance of planning a family., Classification of Evidence: This study provides Class III evidence that for women with relapsing-remitting MS or clinically isolated syndrome who become pregnant, ocrelizumab, rituximab, and natalizumab (continued ≥28 weeks of gestation and restarted ≤1 month postpartum) were associated with reduced risk of relapses, compared with other therapeutic strategies.

Aims: Multiple sclerosis treatment strategies are changing in the Czech Republic. According to data from 2013-2021, the proportion of patients starting high-efficacy disease-modifying therapies is increasing. In this survey, we describe the actual data trends in multiple sclerosis (MS) patients beginning their first disease‑modifying therapies (DMTs) from 2013 to 2021. The secondary objective was to present the history, data collection, and scientific potential of the Czech National MS registry (ReMuS)., Methods: First, using descriptive statistics, we analysed the data for patients starting their first DMTs, either platform (including dimethyl fumarate) or high-efficacy DMTs (HE-DMTs), for each successive year. Second, a detailed description of the history, data collection, completeness, quality optimising procedures, and legal policies of ReMuS is provided., Results: Based on the dataset from December 31, 2021, the total number of monitored patients with MS in ReMuS increased from 9,019 in 2013 (referred from 7 of 15 MS centres) to 12,940 in 2016 (referred from all 15 Czech MS centres) to 17,478 in 2021. In these years, the percentage of patients treated with DMTs in the registry ranged from 76 to 83%, but the proportion of patients treated with HE-DMTs changed from 16.2% in 2013 to 37.1% in 2021. During the follow-up period, a total of 8,491 treatment-naive patients received DMTs. The proportion of patients (all MS phenotypes) starting HE-DMTs increased from 2.1% in 2013 to 18.5% in 2021., Conclusion: Patient registries, including ReMuS, provide an essential quality data source, especially in light of the increasing percentage of patients on HE-DMTs. Although early initiation of HE-DMT can provide considerable benefits, it also carries greater potential risks. Consistent long-term follow-up of patients in real‑world clinical practice, which only registries allow, is therefore crucial to evaluate the efficacy and safety of therapeutic strategies, for epidemiological research and to assist decision making by healthcare providers and regulatory bodies., Competing Interests: The authors report no conflicts of interest in this work.

Background: Disability progression is a key milestone in the disease evolution of people with multiple sclerosis (PwMS). Prediction models of the probability of disability progression have not yet reached the level of trust needed to be adopted in the clinic. A common benchmark to assess model development in multiple sclerosis is also currently lacking., Methods: Data of adult PwMS with a follow-up of at least three years from 146 MS centers, spread over 40 countries and collected by the MSBase consortium was used. With basic inclusion criteria for quality requirements, it represents a total of 15, 240 PwMS. External validation was performed and repeated five times to assess the significance of the results. Transparent Reporting for Individual Prognosis Or Diagnosis (TRIPOD) guidelines were followed. Confirmed disability progression after two years was predicted, with a confirmation window of six months. Only routinely collected variables were used such as the expanded disability status scale, treatment, relapse information, and MS course. To learn the probability of disability progression, state-of-the-art machine learning models were investigated. The discrimination performance of the models is evaluated with the area under the receiver operator curve (ROC-AUC) and under the precision recall curve (AUC-PR), and their calibration via the Brier score and the expected calibration error. All our preprocessing and model code are available at https://gitlab.com/edebrouwer/ms_benchmark, making this task an ideal benchmark for predicting disability progression in MS., Findings: Machine learning models achieved a ROC-AUC of 0⋅71 ± 0⋅01, an AUC-PR of 0⋅26 ± 0⋅02, a Brier score of 0⋅1 ± 0⋅01 and an expected calibration error of 0⋅07 ± 0⋅04. The history of disability progression was identified as being more predictive for future disability progression than the treatment or relapses history., Conclusions: Good discrimination and calibration performance on an external validation set is achieved, using only routinely collected variables. This suggests machine-learning models can reliably inform clinicians about the future occurrence of progression and are mature for a clinical impact study., Competing Interests: The authors declare no competing non-financial interests but the following competing financial interests: - Dana Horakova received speaker honoraria and consulting fees from Biogen, Merck, Teva, Roche, Sanofi Genzyme, and Novartis, as well as support for research activities from Biogen and Czech Minsitry of Education [project Progres Q27/LF1]. - Francesco Patti received speaker honoraria and advisory board fees from Almirall, Bayer, Biogen, Celgene, Merck, Novartis, Roche, Sanofi-Genzyme and TEVA. He received research funding from Biogen, Merck, FISM (Fondazione Italiana Sclerosi Multipla), Reload Onlus Association and University of Catania. - Guillermo Izquierdo received speaking honoraria from Biogen, Novartis, Sanofi, Merck, Roche, Almirall and Teva. - Sara Eichau received speaker honoraria and consultant fees from Biogen Idec, Novartis, Merck, Bayer, Sanofi Genzyme, Roche and Teva. - Marc Girard received consulting fees from Teva Canada Innovation, Biogen, Novartis and Genzyme Sanofi; lecture payments from Teva Canada Innovation, Novartis and EMD. He has also received a research grant from Canadian Institutes of Health Research. - Alessandra Lugaresi has served as a Biogen, Bristol Myers Squibb, Merck Serono, Novartis, Roche, Sanofi/ Genzyme and Teva Advisory Board Member. She received congress and travel/accommodation expense compensations or speaker honoraria from Biogen, Merck, Mylan, Novartis, Roche, Sanofi/Genzyme, Teva and Fondazione Italiana Sclerosi Multipla (FISM). Her institutions received research grants from Novartis and Sanofi Genzyme. - Pierre Grammond has served in advisory boards for Novartis, EMD Serono, Roche, Biogen idec, Sanofi Genzyme, Pendopharm and has received grant support from Genzyme and Roche, has received research grants for his institution from Biogen idec, Sanofi Genzyme, EMD Serono. - Tomas Kalincik served on scientific advisory boards for BMS, Roche, Janssen, Sanofi Genzyme, Novartis, Merck and Biogen, steering committee for Brain Atrophy Initiative by Sanofi Genzyme, received conference travel support and/or speaker honoraria from WebMD Global, Eisai, Novartis, Biogen, Sanofi-Genzyme, Teva, BioCSL and Merck and received research or educational event support from Biogen, Novartis, Genzyme, Roche, Celgene and Merck. - Raed Alroughani received honoraria as a speaker and for serving on scientific advisory boards from Bayer, Biogen, GSK, Merck, Novartis, Roche and Sanofi-Genzyme. - Francois Grand’Maison received honoraria or research funding from Biogen, Genzyme, Novartis, Teva Neurosciences, Mitsubishi and ONO Pharmaceuticals. - Murat Terzi received travel grants from Novartis, Bayer-Schering, Merck and Teva; has participated in clinical trials by Sanofi Aventis, Roche and Novartis. - Jeannette Lechner-Scott travel compensation from Novartis, Biogen, Roche and Merck. Her institution receives the honoraria for talks and advisory board commitment as well as research grants from Biogen, Merck, Roche, TEVA and Novartis. - Samia J. Khoury received compensation for participation in the Novartis Maestro program. - Vincent van Pesch has received travel grants from Merck, Biogen, Sanofi, Bristol Myers Squibb, Almirall and Roche; his institution receives honoraria for consultancy and lectures and research grants from Roche, Biogen, Sanofi, Merck, Bristol Myers Squibb, Janssen, Almirall and Novartis Pharma. - Radek Ampapa received conference travel support from Novartis, Teva, Biogen, Bayer and Merck and has participated in a clinical trials by Biogen, Novartis, Teva and Actelion. - Daniele Spitaleri received honoraria as a consultant on scientific advisory boards by Bayer-Schering, Novartis and Sanofi-Aventis and compensation for travel from Novartis, Biogen, Sanofi Aventis, Teva and Merck. - Claudio Solaro served on scientific advisory boards for Merck, Genzyme, Almirall, and Biogen; received honoraria and travel grants from Sanofi Aventis, Novartis, Biogen, Merck, Genzyme and Teva. - Davide Maimone served on scientific advisory boards for Bayer, Biogen, Merck, Sanofi-Genzyme, Novartis, Roche, and Almirall; received honoraria and travel grants from Sanofi Genzyme, Novartis, Biogen, Merck, and Roche. - Gerardo Iuliano (retired - no PI successor but has approved ongoing use of data) had travel/accommodations/meeting expenses funded by Bayer Schering, Biogen, Merck, Novartis, Sanofi Aventis, and Teva. - Bart Van Wijmeersch received research and travel grants, honoraria for MS-Expert advisor and Speaker fees from Bayer-Schering, Biogen, Sanofi Genzyme, Merck, Novartis, Roche and Teva. - Tamara Castillo Triviño received speaking/consulting fees and/or travel funding from Bayer, Biogen, Merck, Novartis, Roche, Sanofi-Genzyme and Teva. - Jose Luis Sanchez-Menoyo accepted travel compensation from Novartis, Merck and Biogen, speaking honoraria from Biogen, Novartis, Sanofi, Merck, Almirall, Bayer and Teva and has participated in clinical trials by Biogen, Merck and Roche - Guy Laureys received travel and/or consultancy compensation from Sanofi-Genzyme, Roche, Teva, Merck, Novartis, Celgene, Biogen. - Anneke van der Walt served on advisory boards and receives unrestricted research grants from Novartis, Biogen, Merck and Roche She has received speaker’s honoraria and travel support from Novartis, Roche, and Merck. She receives grant support from the National Health and Medical Research Council of Australia and MS Research Australia. - Jiwon Oh has received research funding from the MS Society of Canada, National MS Society, Brain Canada, Biogen, Roche, EMD Serono (an affiliate of Merck KGaA); and personal compensation for consulting or speaking from Alexion, Biogen, Celgene (BMS), EMD Serono (an affiliate of Merck KGaA), Novartis, Roche, and Sanofi-Genzyme. - Ayse Altintas received speaker honoraria from Merck, Alexion,; received travel and registration grants from Merck, Biogen - Gen Pharma, Roche, Sanofi-Genzyme. - Yara Fragoso received honoraria as a consultant on scientific advisory boards by Novartis, Teva, Roche and Sanofi-Aventis and compensation for travel from Novartis, Biogen, Sanofi Aventis, Teva, Roche and Merck. - Tunde Csepany received speaker honoraria/ conference travel support from Bayer Schering, Biogen, Merck, Novartis, Roche, Sanofi-Aventis and Teva. - Suzanne Hodgkinson received honoraria and consulting fees from Novartis, Bayer Schering and Sanofi, and travel grants from Novartis, Biogen Idec and Bayer Schering. - Norma Deri received funding from Bayer, Merck, Biogen, Genzyme and Novartis. - Bruce Taylor received funding for travel and speaker honoraria from Bayer Schering Pharma, CSL Australia, Biogen and Novartis, and has served on advisory boards for Biogen, Novartis, Roche and CSL Australia. - Fraser Moore participated in clinical trials sponsored by EMD Serono and Novartis. - Orla Gray received honoraria as consultant on scientific advisory boards for Genzyme, Biogen, Merck, Roche and Novartis; has received travel grants from Biogen, Merck, Roche and Novartis; has participated in clinical trials by Biogen and Merck. - Csilla Rozsa received speaker honoraria from Bayer Schering, Novartis and Biogen, congress and travel expense compensations from Biogen, Teva, Merck and Bayer Schering. - Allan Kermode received speaker honoraria and scientific advisory board fees from Bayer, BioCSL, Biogen, Genzyme, Innate Immunotherapeutics, Merck, Novartis, Sanofi, Sanofi-Aventis, and Teva. - Magdolna Simo received speaker honoraria from Novartis, Biogen, Bayer Schering; congress/travel compensation from Teva, Biogen, Merck, Bayer Schering. - Todd Hardy has received speaking fees or received honoraria for serving on advisory boards for Biogen, Merck, Teva, Novartis, Roche, Bristol-Myers Squibb and Sanofi-Genzyme, is Co-Editor of Advances in Clinical Neurosciences and Rehabilitation, and serves on the editorial board of Journal of Neuroimmunology and Frontiers in Neurology. - Nikolaos Grigoriadis received honoraria, consultancy/lecture fees, travel support and research grants from Biogen Idec, Biologix, Novartis, TEVA, Bayer, Merck Serono, Genesis Pharma, Sanofi – Genzyme, ROCHE, Cellgene, ELPEN and research grants from Hellenic Ministry of Development., (Copyright: © 2024 De Brouwer et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: Cladribine, a selective immune reconstitution therapy, is approved for the treatment of adult patients with highly active multiple sclerosis (MS)., Objectives: Provide experience with cladribine therapy in a real-world setting., Methods: This is a registry-based retrospective observational cohort study. First, using data from the Czech nationwide registry ReMuS, we analysed patients who initiated cladribine from September 1, 2018 to December 31, 2021. Second, we analysed a subgroup of patients who initiated cladribine between September 1, 2018 to June 30, 2020, thus possessing a follow-up period of at least 2 years. We evaluated demographic and MS characteristics including disease-modifying therapies (DMTs) before and after cladribine administration, relapses, Expanded Disability Status Scale (EDSS), and adherence., Results: In total, 617 patients (335 with follow-up of at least 2 years) started cladribine therapy in the study period (mean age 37.0, mean disease duration 8.4 years, 74.1% females). In most cases, cladribine was administered as a second-line drug, a total of 80.7% had been escalated from a platform DMT. During 2 years before cladribine initiation, the average annualised relapse rate (ARR) was .67. Following cladribine initiation, the ARR decreased to .28 in the first year and .22 in the second year. Overall, across the entire two-year treatment period, 69.0% of patients were relapse-free and the average ARR was .25. As for EDSS development, the median baseline EDSS was 2.5 and remained stable even after 24 months. The adherence to treatment ranged of around 90%., Conclusion: This nationwide study confirms the efficacy of cladribine in real-world settings, especially in patients who are not treatment-naïve. In addition, the study shows an exceptionally high adherence rate, a finding that underscores the invaluable role of cladribine, but also the value of registry-based studies in capturing real-world clinical practice., Competing Interests: The authors declared potential conflicts of interest with respect to the research, authorship and/or publication of this article as following: PP received compensations for travel, speaker honoraria and consultant fees from Biogen Idec, Novartis, Merck Serono, Roche, Sanofi Genzyme. JD has nothing to disclose. DH received compensations for travel, speaker honoraria and consultant fees from Biogen Idec, Novartis, Merck Serono, Roche, Sanofi Genzyme, Teva and Janssen Cilag. MP received compensations for travel, speaker honoraria and consultant fees from Biogen Idec, Novartis, Merck Serono, Roche, Sanofi Genzyme, Teva and Janssen Cilag. AM has nothing to disclose. DM has nothing to disclose. ZP received compensations for travel, speaker honoraria and consultant fees from Biogen Idec, Novartis, Merck Serono, Roche, Sanofi Genzyme, Teva and Janssen Cilag. MV received compensations for travel, speaker honoraria and consultant fees from Biogen Idec, Novartis, Merck Serono, Roche, Sanofi Genzyme, Teva and Janssen Cilag. ER received compensations for travel, speaker honoraria and consultant fees from Biogen Idec, Novartis, Merck Serono, Roche, Sanofi Genzyme, Teva and Janssen Cilag. IS received compensations for travel, speaker honoraria and consultant fees from Biogen Idec, Novartis, Merck Serono, Roche, Sanofi Genzyme, Teva and Janssen Cilag. JL received compensations for travel, speaker honoraria and consultant fees from Biogen Idec, Novartis, Merck Serono, Roche, Sanofi Genzyme, Teva and Janssen Cilag. JM received compensations for travel, speaker honoraria and consultant fees from Biogen Idec, Novartis, Merck Serono, Roche, Sanofi Genzyme, Teva and Janssen Cilag. PS received compensations for travel, speaker honoraria and consultant fees from Biogen Idec, Novartis, Merck Serono, Roche, Sanofi Genzyme, Teva and Janssen Cilag. MG received compensations for travel, speaker honoraria and consultant fees from Biogen Idec, Novartis, Merck Serono, Roche, Sanofi Genzyme, Teva and Janssen Cilag. AM received compensations for travel, speaker honoraria and consultant fees from Biogen Idec, Novartis, Merck Serono, Roche, Sanofi Genzyme, Teva and Janssen Cilag. JA received compensations for travel, speaker honoraria and consultant fees from Biogen Idec, Novartis, Merck Serono, Roche, Sanofi Genzyme, Teva and Janssen Cilag. PH received compensations for travel, speaker honoraria and consultant fees from Biogen Idec, Novartis, Merck Serono, Roche, Sanofi Genzyme, Teva and Janssen Cilag. RA received compensations for travel, speaker honoraria and consultant fees from Biogen Idec, Novartis, Merck Serono, Roche, Sanofi Genzyme, Teva and Janssen Cilag. MD received compensations for travel, speaker honoraria and consultant fees from Biogen Idec, Novartis, Merck Serono, Roche, Sanofi Genzyme, Teva and Janssen Cilag. EKH received compensations for travel, speaker honoraria and consultant fees from Biogen Idec, Novartis, Merck Serono, Roche, Sanofi Genzyme, Teva and Janssen Cilag. DS received compensations for travel, speaker honoraria and consultant fees from Biogen Idec, Novartis, Merck Serono, Roche, Sanofi Genzyme, Teva and Janssen Cilag., (© The Author(s) 2024.)

It is unknown whether the currently known risk factors of multiple sclerosis reflect the etiology of progressive-onset multiple sclerosis (POMS) as observational studies rarely included analysis by type of onset. We designed a case-control study to examine associations between environmental factors and POMS and compared effect sizes to relapse-onset MS (ROMS), which will offer insights into the etiology of POMS and potentially contribute to prevention and intervention practice. This study utilizes data from the Primary Progressive Multiple Sclerosis (PPMS) Study and the Australian Multi-center Study of Environment and Immune Function (the AusImmune Study). This report outlines the conduct of the PPMS Study, whether the POMS sample is representative, and the planned analysis methods. The study includes 155 POMS, 204 ROMS, and 558 controls. The distributions of the POMS were largely similar to Australian POMS patients in the MSBase Study, with 54.8% female, 85.8% POMS born before 1970, mean age of onset of 41.44 ± 8.38 years old, and 67.1% living between 28.9 and 39.4° S. The POMS were representative of the Australian POMS population. There are some differences between POMS and ROMS/controls (mean age at interview: POMS 55 years vs. controls 40 years; sex: POMS 53% female vs. controls 78% female; location of residence: 14.3% of POMS at a latitude ≤ 28.9°S vs. 32.8% in controls), which will be taken into account in the analysis. We discuss the methodological issues considered in the study design, including prevalence-incidence bias, cohort effects, interview bias and recall bias, and present strategies to account for it. Associations between exposures of interest and POMS/ROMS will be presented in subsequent publications., (© 2023. The Author(s).)

Aim: To evaluate the real-world comparative effectiveness and the cost-effectiveness, from a UK National Health Service perspective, of natalizumab versus fingolimod in patients with rapidly evolving severe relapsing-remitting multiple sclerosis (RES-RRMS)., Methods: Real-world data from the MSBase Registry were obtained for patients with RES-RRMS who were previously either naive to disease-modifying therapies or had been treated with interferon-based therapies, glatiramer acetate, dimethyl fumarate, or teriflunomide (collectively known as BRACETD). Matched cohorts were selected by 3-way multinomial propensity score matching, and the annualized relapse rate (ARR) and 6-month-confirmed disability worsening (CDW6M) and improvement (CDI6M) were compared between treatment groups. Comparative effectiveness results were used in a cost-effectiveness model comparing natalizumab and fingolimod, using an established Markov structure over a lifetime horizon with health states based on the Expanded Disability Status Scale. Additional model data sources included the UK MS Survey 2015, published literature, and publicly available sources., Results: In the comparative effectiveness analysis, we found a significantly lower ARR for patients starting natalizumab compared with fingolimod (rate ratio [RR] = 0.65; 95% confidence interval [CI], 0.57-0.73) or BRACETD (RR = 0.46; 95% CI, 0.42-0.53). Similarly, CDI6M was higher for patients starting natalizumab compared with fingolimod (hazard ratio [HR] = 1.25; 95% CI, 1.01-1.55) and BRACETD (HR = 1.46; 95% CI, 1.16-1.85). In patients starting fingolimod, we found a lower ARR (RR = 0.72; 95% CI, 0.65-0.80) compared with starting BRACETD, but no difference in CDI6M (HR = 1.17; 95% CI, 0.91-1.50). Differences in CDW6M were not found between the treatment groups. In the base-case cost-effectiveness analysis, natalizumab dominated fingolimod (0.302 higher quality-adjusted life-years [QALYs] and £17,141 lower predicted lifetime costs). Similar cost-effectiveness results were observed across sensitivity analyses., Conclusions: This MSBase Registry analysis suggests that natalizumab improves clinical outcomes when compared with fingolimod, which translates to higher QALYs and lower costs in UK patients with RES-RRMS.

Background: Treatment switching is a common challenge and opportunity in real-world clinical practice. Increasing diversity in disease-modifying treatments (DMTs) has generated interest in the identification of reliable and robust predictors of treatment switching across different countries, DMTs, and time periods., Objective: The objective of this retrospective, observational study was to identify independent predictors of treatment switching in a population of relapsing-remitting MS (RRMS) patients in the Big Multiple Sclerosis Data Network of national clinical registries, including the Italian MS registry, the OFSEP of France, the Danish MS registry, the Swedish national MS registry, and the international MSBase Registry., Methods: In this cohort study, we merged information on 269,822 treatment episodes in 110,326 patients from 1997 to 2018 from five clinical registries. Patients were included in the final pooled analysis set if they had initiated at least one DMT during the relapsing-remitting MS (RRMS) stage. Patients not diagnosed with RRMS or RRMS patients not initiating DMT therapy during the RRMS phase were excluded from the analysis. The primary study outcome was treatment switching. A multilevel mixed-effects shared frailty time-to-event model was used to identify independent predictors of treatment switching. The contributing MS registry was included in the pooled analysis as a random effect., Results: Every one-point increase in the Expanded Disability Status Scale (EDSS) score at treatment start was associated with 1.08 times the rate of subsequent switching, adjusting for age, sex, and calendar year (adjusted hazard ratio [aHR] 1.08; 95% CI 1.07-1.08). Women were associated with 1.11 times the rate of switching relative to men (95% CI 1.08-1.14), whilst older age was also associated with an increased rate of treatment switching. DMTs started between 2007 and 2012 were associated with 2.48 times the rate of switching relative to DMTs that began between 1996 and 2006 (aHR 2.48; 95% CI 2.48-2.56). DMTs started from 2013 onwards were more likely to switch relative to the earlier treatment epoch (aHR 8.09; 95% CI 7.79-8.41; reference = 1996-2006)., Conclusion: Switching between DMTs is associated with female sex, age, and disability at baseline and has increased in frequency considerably in recent years as more treatment options have become available. Consideration of a patient's individual risk and tolerance profile needs to be taken into account when selecting the most appropriate switch therapy from an expanding array of treatment choices., Competing Interests: TSp received compensation for serving on scientific advisory boards, honoraria for consultancy and funding for travel from Biogen; and speaker honoraria from Novartis. MM has served on the scientific advisory board for Sanofi, Novartis, and Merck and has received honoraria for lecturing from Biogen, Merck, Novartis, Roche, Genzyme, and Bristol Myers Squibb. HB is an employee of Monash University and has accepted travel compensation from Merck; his institution receives honoraria for talks, steering committee activities, and research grants from Roche, Merck, Biogen, Novartis, UCB Pharma, Medical Research Future Fund Australia, NHMRC Australia, Trish MS Foundation, MS Australia, and the Pennycook Foundation. He receives personal compensation for steering group activities for the Brain Health Initiative from the Oxford Health Policy Forum and is funded by an NHMRC Australia Investigator Grant. SV received consulting and lecturing fees, travel grants, and research support from Biogen, Celgene, Genentech, Genzyme, Medday Pharmaceuticals, Merck Serono, Novartis, Roche, Sanofi Aventis, and Teva Pharma. MT has served on scientific advisory boards for Biogen, Novartis, Roche, and Genzyme; has received speaker honoraria and travel support from Biogen Idec, Sanofi Aventis, Merck Serono, Teva, Genzyme, and Novartis; and has received research grants for her institution from Biogen Idec, Merck Serono, and Novartis. PI has served on scientific advisory boards for Biogen Idec, Bayer, Teva, Roche, Merck Serono, Novartis, and Genzyme and has received funding for travel and/or speaker honoraria from Sanofi Aventis, Genzyme, Biogen Idec, Teva, Merck Serono, and Novartis. DH was supported by the Charles University Cooperation Program in Neuroscience, the project National Institute for Neurological Research (Programme EXCELES, ID Project No. LX22NPO5107) funded by the European Union (Next Generation EU), and by the General University Hospital in Prague project MH CZ-DRO-VFN64165. She also received compensation for travel, speaker honoraria, and consultant fees from Biogen Idec, Novartis, Merck, Bayer, Sanofi Genzyme, Roche, and Teva, as well as support for research activities from Biogen Idec. FP is an employee of Biogen. RH is an employee of Biogen and holds stock. PD served on editorial boards and has been supported to attend meetings by EMD, Biogen, Novartis, Genzyme, and TEVA Neuroscience. He holds grants from the CIHR and the MS Society of Canada and has received funding for investigator-initiated trials from Biogen, Novartis, and Genzyme. JL-S received travel compensation from Novartis, Biogen, Roche, and Merck. Her institution receives honoraria for talks and advisory board commitments, as well as research grants from Biogen, Merck, Roche, TEVA, and Novartis. SS declared no competing interests. PL received honoraria for speaking and/or travel expenses from Biogen, Merck, Novartis, Roche; consulting fees from Biogen, GeNeuro, Merck, Novartis, Roche; and research support from Biogen, Merck, Novartis. None were related to this work. SE received speaker honoraria and consultant fees from Biogen Idec, Novartis, Merck, Bayer, Sanofi Genzyme, Roche, and Teva. RAI received honoraria as a speaker and for serving on scientific advisory boards from Bayer, Biogen, GSK, Merck, Novartis, Roche, and Sanofi-Genzyme. MT received travel grants from Novartis, Bayer-Schering, Merck, and Teva; and has participated in clinical trials by Sanofi Aventis, Roche, and Novartis. MG received consulting fees from Teva Canada Innovation, Biogen, Novartis, and Genzyme Sanofi; and lecture payments from Teva Canada Innovation, Novartis, and EMD. He has also received a research grant from the Canadian Institutes of Health Research. TK served on scientific advisory boards for MS International Federation and World Health Organization, BMS, Roche, Janssen, Sanofi Genzyme, Novartis, Merck, and Biogen; on the steering committee for Brain Atrophy Initiative by Sanofi Genzyme, received conference travel support and/or speaker honoraria from WebMD Global, Eisai, Novartis, Biogen, Roche, Sanofi-Genzyme, Teva, BioCSL, and Merck and received research or educational event support from Biogen, Novartis, Genzyme, Roche, Celgene, and Merck. FG received honoraria or research funding from Biogen, Genzyme, Novartis, Teva Neurosciences, and ATARA Pharmaceuticals. OS received honoraria and consulting fees from Bayer-Schering, Novartis, Merck, Biogen, and Genzyme. SK received compensation for scientific advisory board activity from Merck and Roche. BY received honoraria as a speaker and member of scientific advisory boards from Sanofi, Bayer, Biogen, Merck, Janssen, Novartis, Roche, and Aspen. MJ received consulting fees, speaker honoraria, and/or travel expenses for scientific meetings from Alexion, Bayer Healthcare, Biogen, Bristol Myers Squibb, Celgene, Janssen, Merck Serono, Novartis, Roche, Sanofi, and Teva. YB received speaker honoraria/consulting fees from Merck, Biogen, Roche, Bristol Myers Squibb, Novartis, Sanofi, and Sandoz. CO-G received honoraria as a consultant on scientific advisory boards from Biogen, Celgene, Merck, Novartis, Roche, Sanofi-Genzyme, and TEVA. AA received speaker honoraria from Novartis and Alexion. SH has received unrestricted educational grants or speaking honoraria from Biogen, Merck Serono, Novartis, Roche, and Sanofi Genzyme. PM received speaker fees and travel grants from Novartis, Biogen, T'évalua, and Sanofi. RAm received conference travel support from Novartis, Teva, Biogen, Bayer, and Merck and has participated in clinical trials by Biogen, Novartis, Teva, and Actelion. KdG served on scientific advisory boards for Roche, Janssen, Sanofi-Genzyme, Novartis, and Merck, received conference fees and travel support from Novartis, Biogen, Sanofi-Genzyme, Teva, AbbVie, and Merck, and received educational event support from Novartis. CM received honoraria as a consultant on scientific advisory boards for Genzyme, BMS, Janssen, Biogen, Merck, Roche, and Novartis; has received travel grants from Roche and Novartis. JP accepted travel compensation from Novartis, Biogen, Genzyme, Teva, and speaking honoraria from Biogen, Novartis, Genzyme, and Teva. NJ is a local principal investigator on commercial studies funded by Novartis, Biogen, Amicus, and Sanofi. JI declared no competing interests. FS has served on scientific advisory boards for, served as a consultant for, received support for congress participation, or received speaker honoraria from Alexion, Biogen, Bristol Myers Squibb, Merck, Novartis, Roche, and Sanofi Genzyme. His laboratory has received research support from Biogen, Merck, Novartis, Roche, and Sanofi Genzyme. HJ declared no competing interests. PR has served on scientific advisory boards for, served as consultant for, received support for congress participation, or received speaker honoraria from Alexion, Biogen, Bristol Myers Squibb, Merck, Novartis, Roche, and Sanofi Genzyme. TSe received and has served on scientific advisory boards for, served as a consultant for, received support for congress participation, or received speaker honoraria from Biogen, Merck, Novartis, Roche, and Sanofi. T. Sejbaeks received unrestricted research grants to his research institution from Biogen, Merck, and Roche and is currently engaged in sponsor-initiated research projects by Eisai, Lundbeck, Roche, and Sanofi. MP declared no competing interests. JC has received speaker honoraria from Biogen. MS has served on scientific advisory boards for, served as a consultant for, received support for congress participation, participated in industrial trials with, or received speaker honoraria from Bayer, Biogen, Merck, Novartis, Roche, and Sanofi Genzyme. JH has received honoraria for serving on advisory boards for Biogen, Sanofi-Genzyme, and Novartis and speaker's fees from Biogen, Novartis, Merck Serono, Bayer-Schering, Teva, and Sanofi-Genzyme. He has served as P.I. for projects or received unrestricted research support from BiogenIdec, Merck Serono, TEVA, Sanofi-Genzyme, and Bayer-Schering. His MS research is funded by the Swedish Research Council and the Swedish Brain Foundation. The authors declare that this study received funding from Biogen. The funder had the following involvement with the study: study design and manuscript review. The funder was not involved in the collection of data, analysis, writing of the article, or the decision to submit it for publication. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision., (Copyright © 2023 Spelman, Magyari, Butzkueven, Van Der Walt, Vukusic, Trojano, Iaffaldano, Horáková, Drahota, Pellegrini, Hyde, Duquette, Lechner-Scott, Sajedi, Lalive, Shaygannejad, Ozakbas, Eichau, Alroughani, Terzi, Girard, Kalincik, Grand'Maison, Skibina, Khoury, Yamout, Sa, Gerlach, Blanco, Karabudak, Oreja-Guevara, Altintas, Hughes, McCombe, Ampapa, de Gans, McGuigan, Soysal, Prevost, John, Inshasi, Stawiarz, Manouchehrinia, Forsberg, Sellebjerg, Glaser, Pontieri, Joensen, Rasmussen, Sejbaek, Poulsen, Christensen, Kant, Stilund, Mathiesen, Hillert and the Big MS Data Network: a collaboration of the Czech MS Registry, the Danish MS Registry, Italian MS Registry, Swedish MS Registry, MSBase Study Group, and OFSEP.)

Background: Simultaneous comparisons of multiple disease-modifying therapies for relapsing-remitting multiple sclerosis (RRMS) over an extended follow-up are lacking. Here we emulate a randomised trial simultaneously comparing the effectiveness of six commonly used therapies over 5 years., Methods: Data from 74 centres in 35 countries were sourced from MSBase. For each patient, the first eligible intervention was analysed, censoring at change/discontinuation of treatment. The compared interventions included natalizumab, fingolimod, dimethyl fumarate, teriflunomide, interferon beta, glatiramer acetate and no treatment. Marginal structural Cox models (MSMs) were used to estimate the average treatment effects (ATEs) and the average treatment effects among the treated (ATT), rebalancing the compared groups at 6-monthly intervals on age, sex, birth-year, pregnancy status, treatment, relapses, disease duration, disability and disease course. The outcomes analysed were incidence of relapses, 12-month confirmed disability worsening and improvement., Results: 23 236 eligible patients were diagnosed with RRMS or clinically isolated syndrome. Compared with glatiramer acetate (reference), several therapies showed a superior ATE in reducing relapses: natalizumab (HR=0.44, 95% CI=0.40 to 0.50), fingolimod (HR=0.60, 95% CI=0.54 to 0.66) and dimethyl fumarate (HR=0.78, 95% CI=0.66 to 0.92). Further, natalizumab (HR=0.43, 95% CI=0.32 to 0.56) showed a superior ATE in reducing disability worsening and in disability improvement (HR=1.32, 95% CI=1.08 to 1.60). The pairwise ATT comparisons also showed superior effects of natalizumab followed by fingolimod on relapses and disability., Conclusions: The effectiveness of natalizumab and fingolimod in active RRMS is superior to dimethyl fumarate, teriflunomide, glatiramer acetate and interferon beta. This study demonstrates the utility of MSM in emulating trials to compare clinical effectiveness among multiple interventions simultaneously., Competing Interests: Competing interests: The authors report the following relationships: speaker honoraria, advisory board or steering committee fees, research support and/or conference travel support from Acthelion (EKH, RA), Almirall (MT, FG, RB, CRT, JLS-M), Bayer (MT, AL, PS, RA, MT, CB, JL-S, EP, VVP, RB, DS, RA, JO, JLSM, SH, CR, AGK, TC, NS, BT, MS, CAS), BioCSL (TK, AGK, BT), Biogen (TK, TS, DH, EKH, MT, GI, AL, MG, PD, PG, VJ, AVW, FG, PS, DF, RA, RH, CB, JLS, EP, VVP, FG, RB, RA, CRT, JP, JO, MB, JLSM, SH, CR, CSh, OGerlach, AGK, TC, BS, NS, BT, MS, HB), Biologix (RA), BMS/Celgene (EKH, AL), Genpharm (RA), Genzyme-Sanofi (TK, EKH, MT, GI, AL, MG, PD, PG, AVW, FG, PS, DF, RA, RH, MT, CB, JLS, EP, EP, VVP, FG, RB, RB, DS, CRT, JP, JO, MB, JLSM, SH, O Gerlach, AGK, HB), GSK (RA), Innate Immunotherapeutics (AGK), Lundbeck (EP), Merck / EMD (TK, DH, EKH, MT, GI, AL(Merck Serono), MG, PD, PG, VJ, AVW, PS, DF, RA, RH, MT, CB, JLS, EP, VVP, FG, RB, DS, RA, JO, MB, JLSM, CR, FM, O Gerlach, AGK, TC, BS, MS, HB), Mitsubishi (FG),Novartis (TK, TS, DH, EKH, MT, GI, AL, MG, PD, PG, VJ, AVW, FG, PS, DF, RA, RH, MT, CB, JLS, EP, VVP, FG, RB, DS, RA, CRT, JP, JO, MB, JLSM, SH, CR, FM, CSh, OG, AGK, TC, NS, BT, MS, HB), ONO Pharmaceuticals (FG), Roche (TK, EKH, AL, MT, CB, VVP, BT), Teva (TK, DH, EKH, MT, GI, AL, MG, PD, PG, VJ, FG, PS, DF, RH, MT, CB, JLS, VVP, RB, DS, RA, JP, JO, JLSM, CR, AGK, TC, MS, CAS), WebMD (TK), UCB (EP)., (© Author(s) (or their employer(s)) 2023. No commercial re-use. See rights and permissions. Published by BMJ.)

Geographical variations in the incidence and prevalence of multiple sclerosis have been reported globally. Latitude as a surrogate for exposure to ultraviolet radiation but also other lifestyle and environmental factors are regarded as drivers of this variation. No previous studies evaluated geographical variation in the risk of secondary progressive multiple sclerosis, an advanced form of multiple sclerosis that is characterized by steady accrual of irreversible disability. We evaluated differences in the risk of secondary progressive multiple sclerosis in relation to latitude and country of residence, modified by high-to-moderate efficacy immunotherapy in a geographically diverse cohort of patients with relapsing-remitting multiple sclerosis. The study included relapsing-remitting multiple sclerosis patients from the global MSBase registry with at least one recorded assessment of disability. Secondary progressive multiple sclerosis was identified as per clinician diagnosis. Sensitivity analyses used the operationalized definition of secondary progressive multiple sclerosis and the Swedish decision tree algorithm. A proportional hazards model was used to estimate the cumulative risk of secondary progressive multiple sclerosis by country of residence (latitude), adjusted for sex, age at disease onset, time from onset to relapsing-remitting phase, disability (Multiple Sclerosis Severity Score) and relapse activity at study inclusion, national multiple sclerosis prevalence, government health expenditure, and proportion of time treated with high-to-moderate efficacy disease-modifying therapy. Geographical variation in time from relapsing-remitting phase to secondary progressive phase of multiple sclerosis was modelled through a proportional hazards model with spatially correlated frailties. We included 51 126 patients (72% female) from 27 countries. The median survival time from relapsing-remitting phase to secondary progressive multiple sclerosis among all patients was 39 (95% confidence interval: 37 to 43) years. Higher latitude [median hazard ratio = 1.21, 95% credible interval (1.16, 1.26)], higher national multiple sclerosis prevalence [1.07 (1.03, 1.11)], male sex [1.30 (1.22, 1.39)], older age at onset [1.35 (1.30, 1.39)], higher disability [2.40 (2.34, 2.47)] and frequent relapses [1.18 (1.15, 1.21)] at inclusion were associated with increased hazard of secondary progressive multiple sclerosis. Higher proportion of time on high-to-moderate efficacy therapy substantially reduced the hazard of secondary progressive multiple sclerosis [0.76 (0.73, 0.79)] and reduced the effect of latitude [interaction: 0.95 (0.92, 0.99)]. At the country-level, patients in Oman, Tunisia, Iran and Canada had higher risks of secondary progressive multiple sclerosis relative to the other studied regions. Higher latitude of residence is associated with a higher probability of developing secondary progressive multiple sclerosis. High-to-moderate efficacy immunotherapy can mitigate some of this geographically co-determined risk., (© The Author(s) 2023. Published by Oxford University Press on behalf of the Guarantors of Brain.)

Background: Some studies comparing primary and secondary progressive multiple sclerosis (PPMS, SPMS) report similar ages at onset of the progressive phase and similar rates of subsequent disability accrual. Others report later onset and/or faster accrual in SPMS. Comparisons have been complicated by regional cohort effects, phenotypic differences in sex ratio and management and variable diagnostic criteria for SPMS., Methods: We compared disability accrual in PPMS and operationally diagnosed SPMS in the international, clinic-based MSBase cohort. Inclusion required PPMS or SPMS with onset at age ≥18 years since 1995. We estimated Andersen-Gill hazard ratios for disability accrual on the Expanded Disability Status Scale (EDSS), adjusted for sex, age, baseline disability, EDSS score frequency and drug therapies, with centre and patient as random effects. We also estimated ages at onset of the progressive phase (Kaplan-Meier) and at EDSS milestones (Turnbull). Analyses were replicated with physician-diagnosed SPMS., Results: Included patients comprised 1872 with PPMS (47% men; 50% with activity) and 2575 with SPMS (32% men; 40% with activity). Relative to PPMS, SPMS had older age at onset of the progressive phase (median 46.7 years (95% CI 46.2-47.3) vs 43.9 (43.3-44.4); p<0.001), greater baseline disability, slower disability accrual (HR 0.86 (0.78-0.94); p<0.001) and similar age at wheelchair dependence., Conclusions: We demonstrate later onset of the progressive phase and slower disability accrual in SPMS versus PPMS. This may balance greater baseline disability in SPMS, yielding convergent disability trajectories across phenotypes. The different rates of disability accrual should be considered before amalgamating PPMS and SPMS in clinical trials., Competing Interests: Competing interests: IR served on scientific advisory boards for Novartis and Merck, and received conference travel support and/or speaker honoraria from Roche, Novartis, Biogen, Teva, Sanofi Genzyme, and Merck. A-LN received grants from MS Research Australia; grants, personal fees, and nonfinancial support from Biogen; grants and personal fees from Merck Serono; personal fees from Teva and Novartis; and nonfinancial support from Roche and Sanofi Genzyme. GI received speaking honoraria from Biogen, Novartis, Sanofi, Merck, Roche, Almirall, and Teva. SE received speaker honoraria and consultant fees from Biogen Idec, Novartis, Merck, Bayer, Sanofi Genzyme, Roche, and Teva. FP received speaker honoraria and advisory board fees from Almirall, Bayer, Biogen, Celgene, Merck, Novartis, Roche, Sanofi Genzyme, and Teva, and research funding from Biogen, Merck, FISM (Fondazione Italiana Sclerosi Multipla), Reload Onlus Association, and the University of Catania. DH received speaker honoraria and consulting fees from Biogen, Merck, Teva, Roche, Sanofi Genzyme, and Novartis, and support for research activities from Biogen and the Czech Ministry of Education (project PROGRES Q27/LF1). EVH received honoraria or research support from Biogen, Merck Serono, Novartis, Roche, and Teva; has been a member of advisory boards for Actelion, Biogen, Celgene, Merck Serono, Novartis, and Sanofi Genzyme; and received research support from the Czech Ministry of Education (project PROGRES Q27/LF1). MG received consulting fees from Teva Canada Innovation, Biogen, Novartis, and Sanofi Genzyme; lecture payments from Teva Canada Innovation, Novartis, and EMD; and research support from the Canadian Institutes of Health Research. PD served on editorial boards for, and has been supported to attend meetings by, EMD, Biogen, Novartis, Genzyme, and Teva Neuroscience; he holds grants from the Canadian Institutes of Health Research and the MS Society of Canada, and received funding for investigator-initiated trials from Biogen, Novartis, and Genzyme. FG’M received honoraria or research funding from Biogen, Genzyme, Novartis, Teva Neurosciences, Mitsubishi, and ONO Pharmaceuticals. AL received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities from Biogen, Merck Serono, Mylan, Novartis, Roche, Sanofi Genzyme, and Teva; her institutions have received research grants from Novartis (in the past 4 years). PG served on advisory boards for Novartis, EMD Serono, Roche, Biogen Idec, Sanofi Genzyme, and Pendopharm; received grant support from Genzyme and Roche; and received research grants for his institution from Biogen Idec, Sanofi Genzyme, and EMD Serono. MPA received honoraria as a consultant on scientific advisory boards for Biogen, Bayer Schering, Merck, Teva, and Sanofi-Aventis, and received research grants by Biogen, Bayer Schering, Merck, Teva, and Novartis. PS served on scientific advisory boards for Biogen Idec and Teva; received funding for travel and speaker honoraria from Biogen Idec, Merck, Teva, Sanofi Genzyme, Novartis, and Bayer; and received research grants for her institution from Bayer, Biogen, Merck, Novartis, Sanofi, and Teva. DF received travel grants and/or speaker honoraria from Merck, Teva, Novartis, Biogen, and Sanofi Genzyme. KB received honoraria and consulting fees from Biogen, Teva, Novartis, Sanofi Genzyme, Roche, Merck, CSL, and Grifols. JL-S received travel compensation from Novartis, Biogen, Roche, and Merck; her institution received honoraria for talks and advisory board commitments, as well as research grants from Biogen, Merck, Roche, Teva, and Novartis. RA received honoraria as a speaker and for serving on scientific advisory boards from Bayer, Biogen, GSK, Merck, Novartis, Roche, and Sanofi Genzyme. CB received conference travel support from Biogen, Novartis, Bayer Schering, Merck, and Teva, and participated in clinical trials by Sanofi-Aventis, Roche, and Novartis. VVP received travel grants from Merck, Biogen, Sanofi, Celgene, Almirall, and Roche; his institution received research grants and consultancy fees from Roche, Biogen, Sanofi, Celgene, Merck, and Novartis Pharma. MT received travel grants from Novartis, Bayer Schering, Merck, and Teva, and participated in clinical trials by Sanofi-Aventis, Roche, and Novartis. DM received speaker honoraria for advisory board service and travel grants from Almirall, Biogen, Merck, Novartis, Roche, Sanofi Genzyme, and Teva. CR-T received research funding, compensation for travel, or speaker honoraria from Biogen, Novartis, Genzyme, and Almirall. DLS received honoraria as a consultant on scientific advisory boards from Bayer Schering, Novartis, and Sanofi-Aventis, and compensation for travel from Novartis, Biogen, Sanofi-Aventis, Teva, and Merck. FG received an institutional research grant from Biogen and Sanofi Genzyme; served on scientific advisory boards for Biogen, Novartis, Merck, Sanofi Genzyme, and Roche; and received funding for travel and speaker honoraria from Biogen, Merck, and Sanofi-Aventis. MS participated in, but did not receive honoraria for, advisory board activity for Biogen, Merck, Bayer Schering, Sanofi-Aventis, and Novartis. RB received speaker honoraria from Bayer Schering, Biogen, Genzyme, Merck, Novartis, Sanofi-Aventis, and Teva; research grants from Bayer Schering, Biogen, Merck, Novartis, Sanofi-Aventis, and Teva; and congress, travel, and accommodation expense compensations from Almirall, Bayer Schering, Biogen, Genzyme, Merck, Novartis, Sanofi-Aventis, and Teva. RA received conference travel support from Novartis, Teva, Biogen, Bayer, and Merck, and participated in clinical trials by Biogen, Novartis, Teva, and Actelion. JLS-M received travel compensation from Novartis and Biogen; received speaking honoraria from Biogen, Novartis, Sanofi, Merck, Almirall, Bayer, and Teva; and participated in a clinical trial by Biogen. JP received travel compensation from Novartis, Biogen, Genzyme, and Teva, and speaking honoraria from Biogen, Novartis, Genzyme and Teva. TC-T received speaking or consulting fees and/or travel funding from Bayer, Biogen, Merck, Novartis, Roche, Sanofi Genzyme, and Teva. GL received travel and/or consultancy compensation from Sanofi Genzyme, Roche, Teva, Merck, Novartis, Celgene, and Biogen. JO received research funding from the MS Society of Canada, the National MS Society, Brain Canada, Biogen Idec, Roche, and EMD Serono, and personal compensation for consulting or speaking from EMD Serono, Sanofi Genzyme, Biogen Idec, Roche, Celgene, and Novartis. AA received personal fees and speaker honoraria from Teva, Merck, Biogen Gen Pharma, Roche, Novartis, Bayer, and Sanofi Genzyme, and received travel and registration grants from Merck, Biogen Gen Pharma, Roche, Sanofi Genzyme, and Bayer. HB received compensation for consulting, talks, and advisory or steering board activities from Biogen, Merck, Novartis, Genzyme, Alfred Health, and Oxford Health Policy Forum, and research support from Novartis, Biogen, Roche, Merck, the National Health and Medical Research Council of Australia, Pennycook Foundation, and MS Research Australia MB served on scientific advisory boards for Biogen, Novartis, and Genzyme, received conference travel support from Biogen and Novartis, and serves on steering committees for trials conducted by Novartis; his institution received research support from Biogen, Merck, and Novartis. EC Cristiano received honoraria as a consultant on scientific advisory boards for Biogen, Bayer Schering, Merck, Genzyme, and Novartis, and participated in clinical trials or other research projects by Merck, Roche, and Novartis. SH received honoraria and consulting fees from Novartis, Bayer Schering, and Sanofi, and travel grants from Novartis, Biogen Idec, and Bayer Schering. GI received compensation for travel, accommodations, and meeting expenses from Bayer Schering, Biogen, Merck, Novartis, Sanofi-Aventis, and Teva. LK received research support from Acorda, Actelion, Allozyne, BaroFold, Bayer HealthCare, Bayer Schering, Bayhill Therapeutics, Biogen, Elan, European Union, Genmab, Gianni Rubatto Foundation, GlaxoSmithKline, Glenmark, MediciNova, Merck, Novartis, Novartis Research Foundation, Roche, Roche Research Foundation, Sanofi-Aventis, Santhera, the Swiss MS Society, the Swiss National Research Foundation, Teva Neuroscience, UCB, and Wyeth. BW-G participated in speakers' bureaus and/or served as a consultant for Biogen, EMD Serono, Novartis, Genentech, Celgene/Bristol Meyers Squibb, Sanofi Genzyme, Bayer, Janssen, and Horizon; received grant/research support from these same agencies; and serves on editorial boards for BMJ Neurology, Children, CNS Drugs, MS International, and Frontiers Epidemiology. BVW received research and travel grants and honoraria for advisory and speaking fees from Bayer Schering, Biogen, Sanofi Genzyme, Merck, Novartis, Roche, and Teva. TK served on scientific advisory boards for BMS, Roche, Sanofi Genzyme, Novartis, Merck, and Biogen, and the steering committee for the Brain Atrophy Initiative by Sanofi Genzyme; received conference travel support and/or speaker honoraria from WebMD Global, Novartis, Biogen, Sanofi Genzyme, Teva, BioCSL, and Merck; and received support for research or educational events from Biogen, Novartis, Genzyme, Roche, Celgene, and Merck., (© Author(s) (or their employer(s)) 2023. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: In relapsing-remitting multiple sclerosis (RRMS) the most common treatment strategy has been to start with low-moderate efficacy disease modifying therapy (LE-DMT) and to escalate to more efficacious treatments in cases of breakthrough disease activity. However, recent evidence suggests a better outcome in patients commencing with moderate-high efficacy DMT (HE-DMT) immediately after clinical onset., Objective: The aim of this study is to compare disease activity and disability outcomes in patients treated with the two alternative strategies using the Swedish and Czech national multiple sclerosis registries, taking advantage of the fact that the relative frequency of each strategy differs markedly between these two countries., Methods: Adult RRMS patients who initiated their first-ever DMT between 2013 and 2016 and were included in the Swedish MS register were compared with a similar cohort from the MS register of the Czech Republic using propensity score overlap weighting as a balancing method. The main outcomes of interest were time to confirmed disability worsening (CDW), time to achieve an expanded disability status scale (EDSS) value of 4, time to relapse, and time to confirmed disability improvement (CDI). To support the results, a sensitivity analysis focusing solely on patients from Sweden starting with HE-DMT and patients from the Czech Republic starting with LE-DMT was performed., Results: In the Swedish cohort, 42% of patients received HE-DMT as initial therapy compared to 3.8% of patients in the Czech cohort. The time to CDW was not significantly different between the Swedish and Czech cohorts (p-value 0.2764), with hazard ratio (HR) of 0.89 and a 95% confidence interval (CI) of 0.77-1.03. Patients from the Swedish cohort exhibited better outcomes for all remaining variables. The risk of reaching EDSS 4 was reduced by 26% (HR 0.74, 95%CI 0.6-0.91, p-value 0.0327), the risk of relapse was reduced by 66% (HR 0.34, 95%CI 0.3-0.39, p-value <0.001), and the probability of CDI was three times higher (HR 3.04, 95%CI 2.37-3.9, p-value <0.001)., Conclusion: The analysis of the Czech and the Swedish RRMS cohorts confirmed a better prognosis for patients in Sweden, where a significant proportion of patients received HE-DMT as initial treatment., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: T. Hrnciarova has nothing to disclose. J. Drahota has nothing to disclose. T. Spelman received compensation from serving on scientific advisory boards and steering comittees from Biogen and consultancy fees from Hartmann and Abbvie. J. Hillert received honoraria for serving on advisory boards for Biogen, Bristol-Myers-Squibb/Celgene, Janssen, Merck KGaA, Sandoz and Sanofi-Genzyme and speaker...s fees from Biogen, Janssen, Novartis, Merck, Teva, Sandoz and Sanofi-Genzyme. He has served as P.I. for projects sponsored by, or received unrestricted research support from, Biogen, Bristol-MyersSquibb/Celgene, Janssen, Merck KGaA, Novartis, Roche, and Sanofi-Genzyme. His MS research is funded by the Swedish Research Council and the Swedish Brain foundation. J. Lycke has received travel support and/or lecture honoraria and has served on scientific advisory boards for Alexion, Almirall, Biogen, Bristol Myers Squibb, Celgene, Janssen, Merck, Novartis, Roche and Sanofi; and has received unconditional research grants from Biogen and Novartis, and financial support from Sanofi for an investigator-initiated study. E. Kubala Havrdova has received honoraria/research support from Biogen, Merck Serono, Novartis, Roche, and Teva; has served as a member of advisory boards for Actelion, Biogen, Celgene, Merck Serono, Novartis, and Sanofi Genzyme; has been supported by the Czech Ministry of Education project Cooperatio LF1, research area Neuroscience, and the project National Institute for Neurological Research (Programme EXCELES, ID project No LX22NPO5107) funded by the European Union-Next Generation EU. E. Recmanova has nothing to disclose. J. Adamkova has nothing to disclose. J. Mares has nothing to disclose. J. Libertinova reported receiving grants, personal fees and funding for travel from Merck, Roche, Novartis, Biogen Inc, Sanofi Genzyme. Z. Pavelek reports personal fees from Biogen, Eli Lilly, Genzyme, Merck Serono, Novartis, Pfizer, Roche, and Teva Pharma. P. Hradilek received speakers honoraria and travel compensations from Biogen, Merck, Teva, Sanofi, Roche, Novartis and Janssen Cilag. R. Ampapa received conference travel support from Roche, Sanofi, Biogen and Merck and has participated in clinical trials by Biogen, Novartis, Sanofi, Merck and Roche. I. Stetkarova received compensation for travel and speaker honoraria from Biogen Idec, Merck, and Roche. M. Peterka has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with Merck, Novartis, Biogen, Sanofi-Genzyme, Jansse-Cilag, Teva, Roche. A. Martinkova has nothing to disclose. P. Stourac has nothing to disclose. M. Grunermelova has nothing to disclose. M. Vachova received compensation for travel, conference fees, consulting fees and speaker honoraria from Biogen, Lundbeck, Merck, Novartis, Roche, Sanofi, and Teva. M. Dufek has nothing to disclose. D. Horakova was supported by the Charles University: Cooperatio Program in Neuroscience, by the project National Institute for Neurological Research (Programme EXCELES, ID Project No. LX22NPO5107) - Funded by the European Union Next Generation EU, and by General University Hospital in Prague project MH CZ-DRO-VFN64165. She also received compensation for travel, speaker honoraria and consultant fees from Biogen Idec, Novartis, Merck, Bayer, Sanofi Genzyme, Roche, and Teva, as well as support for research activities from Biogen Idec., (Copyright © 2023. Published by Elsevier B.V.)

What Is This Summary About?: Patient registries contain anonymous data from people who share the same medical condition. The MSBase registry contains information from over 80,000 people living with multiple sclerosis (MS) across 41 countries. Using information from the MSBase registry, the GLIMPSE (Generating Learnings In MultiPle SclErosis) study looked at real-life outcomes in 3475 people living with MS who were treated with cladribine tablets (Mavenclad ® ) compared with other oral treatments., What Were the Results?: Results showed that people treated with cladribine tablets stayed on treatment for longer than other treatments given by mouth. They also had fewer relapses (also called flare ups of symptoms) than people who received a different oral treatment for their MS., What Do the Results Mean?: The results provide evidence that, compared with other oral treatments for MS, cladribine tablets are an effective medicine for people living with MS.

Introduction: The influence of breastfeeding and it´s duration on the course of multiple sclerosis (MS) is unclear. Here we analyzed a real-world data for breastfeeding women with MS and their disease course collected from a Czech national registry ReMuS., Objectives: To identify risk factors associated with not initiating breastfeeding after delivery, to analyze the impact of breastfeeding on the MS disease course, evaluate the assumption, that breastfeeding is not harmful in MS patients, and compare the disease course by breastfeeding status., Materials and Methods: Using propensity score matching we compared Expanded Disability Status Scale (EDSS), confirmed disease worsening (CDW) and annual relapse rate (ARR) in breastfeeding and non-breastfeeding MS patients according to disease duration, disease modifying treatment (DMT) before pregnancy, last EDSS score before conception, age, and ARR during pregnancy. We also compared these parameters between breastfeeding patients not using a DMT and non-breastfeeding patients who resumed DMT within 3 months after delivery. EDSS, ARR, and CDW were collected at 12, 24, and 36 months after delivery., Results: A total of 1681 pregnancies that ended in delivery were analyzed from 2013 through 2020. Change in ARR and EDSS values and 6-months CDW did not significantly differ between the analyzed groups. Compared with non-breastfeeding women who resumed DMT early after delivery, breastfeeding women with MS did not experience worse clinical outcomes even without initiating a DMT., Discussion: Breastfeeding in Czech women with MS did not negatively affect the disease course and can be supported. Patients with MS can be treated with certain DMTs alongside breastfeeding and there is no need to stop breastfeeding, if the patient is clinically stable., Competing Interests: Declaration of Competing Interest The authors declared potential conflicts of interest with respect to the research, authorship and/or publication of this article as following: P.H. received compensations for travel, speaker honoraria and consultant fees from Biogen Idec, Novartis, Merck Serono, Roche, Sanofi Genzyme, Teva and Janssen cilag. O.Z. received compensations for travel, speaker honoraria and consultant fees from Biogen Idec, Novartis, Merck Serono, Roche, Sanofi Genzyme, Teva and Janssen cilag. P.H. has nothing to disclose. E.K.H. received compensations for travel, speaker honoraria and consultant fees from Biogen Idec, Novartis, Merck Serono, Roche, Sanofi Genzyme, Teva and Janssen cilag. I.W. received compensations for travel from Biogen Idec, Novartis, Merck Serono, Roche, Sanofi Genzyme and Teva. A.M. has nothing to disclose. J.D. has nothing to disclose. M.L. has nothing to disclose I.S. received compensations for travel, speaker honoraria and consultant fees from Biogen Idec, Novartis, Merck Serono, Roche, Sanofi Genzyme, Teva and Janssen cilag. M.V. received compensations for travel, speaker honoraria and consultant fees from Biogen Idec, Novartis, Merck Serono, Roche, Sanofi Genzyme, Teva and Janssen cilag. J.L. received compensations for travel and consultant fees from Biogen Idec, Novartis, Merck Serono, Roche, Sanofi Genzyme, Teva and Janssen cilag. P.S. received compensations for travel, speaker honoraria and consultant fees from Biogen Idec, Novartis, Merck Serono, Roche, Sanofi Genzyme, Teva and Janssen cilag. J.A. received compensations for travel from Biogen Idec, Novartis, Merck Serono, Roche, Sanofi Genzyme and Teva. R.A. received compensations for travel, speaker honoraria and consultant fees from Biogen Idec, Novartis, Merck Serono, Roche, Sanofi Genzyme, Teva and Janssen cilag. M.V. received compensations for travel, speaker honoraria and consultant fees from Biogen Idec, Novartis, Merck Serono, Roche, Sanofi Genzyme, Teva and Janssen cilag. M.D. received compensations for travel, speaker honoraria and consultant fees from Biogen Idec, Novartis, Merck Serono, Roche, Sanofi Genzyme, Teva and Janssen cilag. A.M. received compensations for travel, speaker honoraria and consultant fees from Biogen Idec, Novartis, Merck Serono, Roche, Sanofi Genzyme, Teva and Janssen cilag. M.P. received compensations for travel, speaker honoraria and consultant fees from Biogen Idec, Novartis, Merck Serono, Roche, Sanofi Genzyme, Teva and Janssen cilag. J.M. received compensations for travel, speaker honoraria and consultant fees from Biogen Idec, Novartis, Merck Serono, Roche, Sanofi Genzyme, Teva and Janssen cilag. D.H. received compensations for travel, speaker honoraria and consultant fees from Biogen Idec, Novartis, Merck Serono, Roche, Sanofi Genzyme, Teva and Janssen cilag, (Copyright © 2023 Elsevier B.V. All rights reserved.)

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.

Background and Purpose: This study assessed the effect of patient characteristics on the response to disease-modifying therapy (DMT) in multiple sclerosis (MS)., Methods: We extracted data from 61,810 patients from 135 centers across 35 countries from the MSBase registry. The selection criteria were: clinically isolated syndrome or definite MS, follow-up ≥ 1 year, and Expanded Disability Status Scale (EDSS) score ≥ 3, with ≥1 score recorded per year. Marginal structural models with interaction terms were used to compare the hazards of 12-month confirmed worsening and improvement of disability, and the incidence of relapses between treated and untreated patients stratified by their characteristics., Results: Among 24,344 patients with relapsing MS, those on DMTs experienced 48% reduction in relapse incidence (hazard ratio [HR] = 0.52, 95% confidence interval [CI] = 0.45-0.60), 46% lower risk of disability worsening (HR = 0.54, 95% CI = 0.41-0.71), and 32% greater chance of disability improvement (HR = 1.32, 95% CI = 1.09-1.59). The effect of DMTs on EDSS worsening and improvement and the risk of relapses was attenuated with more severe disability. The magnitude of the effect of DMT on suppressing relapses declined with higher prior relapse rate and prior cerebral magnetic resonance imaging activity. We did not find any evidence for the effect of age on the effectiveness of DMT. After inclusion of 1985 participants with progressive MS, the effect of DMT on disability mostly depended on MS phenotype, whereas its effect on relapses was driven mainly by prior relapse activity., Conclusions: DMT is generally most effective among patients with lower disability and in relapsing MS phenotypes. There is no evidence of attenuation of the effect of DMT with age., (© 2023 The Authors. European Journal of Neurology published by John Wiley & Sons Ltd on behalf of European Academy of Neurology.)

Background: In the absence of evidence from randomised controlled trials, observational data can be used to emulate clinical trials and guide clinical decisions. Observational studies are, however, susceptible to confounding and bias. Among the used techniques to reduce indication bias are propensity score matching and marginal structural models., Objective: To use the comparative effectiveness of fingolimod vs natalizumab to compare the results obtained with propensity score matching and marginal structural models., Methods: Patients with clinically isolated syndrome or relapsing remitting MS who were treated with either fingolimod or natalizumab were identified in the MSBase registry. Patients were propensity score matched, and inverse probability of treatment weighted at six monthly intervals, using the following variables: age, sex, disability, MS duration, MS course, prior relapses, and prior therapies. Studied outcomes were cumulative hazard of relapse, disability accumulation, and disability improvement., Results: 4608 patients (1659 natalizumab, 2949 fingolimod) fulfilled inclusion criteria, and were propensity score matched or repeatedly reweighed with marginal structural models. Natalizumab treatment was associated with a lower probability of relapse (PS matching: HR 0.67 [95% CI 0.62-0.80]; marginal structural model: 0.71 [0.62-0.80]), and higher probability of disability improvement (PS matching: 1.21 [1.02 -1.43]; marginal structural model 1.43 1.19 -1.72]). There was no evidence of a difference in the magnitude of effect between the two methods., Conclusions: The relative effectiveness of two therapies can be efficiently compared by either marginal structural models or propensity score matching when applied in clearly defined clinical contexts and in sufficiently powered cohorts.

Background: Effectiveness of cladribine tablets, an oral disease-modifying treatment (DMT) for multiple sclerosis (MS), was established in clinical trials and confirmed with real-world experience., Objectives: Use real-world data to compare treatment patterns and clinical outcomes in people with MS (pwMS) treated with cladribine tablets versus other oral DMTs., Methods: Retrospective treatment comparisons were based on data from the international MSBase registry. Eligible pwMS started treatment with cladribine, fingolimod, dimethyl fumarate, or teriflunomide tablets from 2018 to mid-2021 and were censored at treatment discontinuation/switch, death, loss to follow-up, pregnancy, or study period end. Treatment persistence was evaluated as time to discontinuation/switch; relapse outcomes included time to first relapse and annualized relapse rate (ARR)., Results: Cohorts included 633 pwMS receiving cladribine tablets, 1195 receiving fingolimod, 912 receiving dimethyl fumarate, and 735 receiving teriflunomide. Individuals treated with fingolimod, dimethyl fumarate, or teriflunomide switched treatment significantly more quickly than matched cladribine tablet cohorts (adjusted hazard ratio (95% confidence interval): 4.00 (2.54-6.32), 7.04 (4.16-11.93), and 6.52 (3.79-11.22), respectively). Cladribine tablet cohorts had significantly longer time-to-treatment discontinuation, time to first relapse, and lower ARR, compared with other oral DMT cohorts., Conclusion: Cladribine tablets were associated with a significantly greater real-world treatment persistence and more favorable relapse outcomes than all oral DMT comparators.

Background and Objectives: To evaluate the rate of return of disease activity after cessation of multiple sclerosis (MS) disease-modifying therapy., Methods: This was a retrospective cohort study from 2 large observational MS registries: MSBase and OFSEP. Patients with relapsing-remitting MS who had ceased a disease-modifying therapy and were followed up for the subsequent 12 months were included in the analysis. The primary study outcome was annualized relapse rate in the 12 months after disease-modifying therapy discontinuation stratified by patients who did, and did not, commence a subsequent therapy. The secondary endpoint was the predictors of first relapse and disability accumulation after treatment discontinuation., Results: A total of 14,213 patients, with 18,029 eligible treatment discontinuation epochs, were identified for 7 therapies. Annualized rates of relapse (ARRs) started to increase 2 months after natalizumab cessation (month 2-4 ARR 0.47, 95% CI 0.43-0.51). Commencement of a subsequent therapy within 2-4 months reduced the magnitude of disease reactivation (mean ARR difference: 0.15, 0.08-0.22). After discontinuation of fingolimod, rates of relapse increased overall (month 1-2 ARR: 0.80, 0.70-0.89) and stabilized faster in patients who started a new therapy within 1-2 months (mean ARR difference: 0.14, -0.01 to 0.29). The magnitude of disease reactivation for other therapies was low but reduced further by commencement of another treatment 1-10 months after treatment discontinuation. Predictors of relapse were a higher relapse rate in the year before cessation, female sex, younger age, and higher EDSS score. Commencement of a subsequent therapy reduced both the risk of relapse (HR 0.76, 95% CI 0.72-0.81) and disability accumulation (0.73, 0.65-0.80)., Discussion: The rate of disease reactivation after treatment cessation differs among MS treatments, with the peaks of relapse activity ranging from 1 to 10 months in untreated cohorts that discontinued different therapies. These results suggest that untreated intervals should be minimized after stopping antitrafficking therapies (natalizumab and fingolimod)., Classification of Evidence: This study provides Class III that disease reactivation occurs within months of discontinuation of MS disease-modifying therapies. The risk of disease activity is reduced by commencement of a subsequent therapy., (© 2022 American Academy of Neurology.)

Background: The MSBase prediction model of treatment response leverages multiple demographic and clinical characteristics to estimate hazards of relapses, confirmed disability accumulation (CDA), and confirmed disability improvement (CDI). The model did not include Multiple Sclerosis Severity Score (MSSS), a disease duration-adjusted ranked score of disability., Objective: To incorporate MSSS into the MSBase prediction model and compare model accuracy with and without MSSS., Methods: The associations between MSSS and relapse, CDA, and CDI were evaluated with marginal proportional hazards models adjusted for three principal components representative of patients' demographic and clinical characteristics. The model fit with and without MSSS was assessed with penalized r2 and Harrell C., Results: A total of 5866 MS patients were started on disease-modifying therapy during prospective follow-up (age 38.4 ± 10.6 years; 72% female; disease duration 8.5 ± 7.7 years). Including MSSS into the model improved the accuracy of individual prediction of relapses by 31%, of CDA by 23%, and of CDI by 24% (Harrell C) and increased the amount of variance explained for relapses by 49%, for CDI by 11%, and for CDA by 10% as compared with the original model., Conclusion: Addition of a single, readily available metric, MSSS, to the comprehensive MSBase prediction model considerably improved the individual accuracy of prognostics in MS.

Background and Purpose: The prevention of disability over the long term is the main treatment goal in multiple sclerosis (MS); however, randomized clinical trials evaluate only short-term treatment effects on disability. This study aimed to define criteria for 6-month confirmed disability progression events of MS with a high probability of resulting in sustained long-term disability worsening., Methods: In total, 14,802 6-month confirmed disability progression events were identified in 8741 patients from the global MSBase registry. For each 6-month confirmed progression event (13,321 in the development and 1481 in the validation cohort), a sustained progression score was calculated based on the demographic and clinical characteristics at the time of progression that were predictive of long-term disability worsening. The score was externally validated in the Cladribine Tablets Treating Multiple Sclerosis Orally (CLARITY) trial., Results: The score was based on age, sex, MS phenotype, relapse activity, disability score and its change from baseline, number of affected functional system domains and worsening in six of the domains. In the internal validation cohort, a 61% lower chance of improvement was estimated with each unit increase in the score (hazard ratio 0.39, 95% confidence interval 0.29-0.52; discriminatory index 0.89). The proportions of progression events sustained at 5 years stratified by the score were 1: 72%; 2: 88%; 3: 94%; 4: 100%. The results of the CLARITY trial were confirmed for reduction of disability progression that was &gt;88% likely to be sustained (events with score ˃1.5)., Conclusions: Clinicodemographic characteristics of 6-month confirmed disability progression events identify those at high risk of sustained long-term disability. This knowledge will allow future trials to better assess the effect of therapy on long-term disability accrual., (© 2022 The Authors. European Journal of Neurology published by John Wiley & Sons Ltd on behalf of European Academy of Neurology.)

Background and Objectives: The severity of multiple sclerosis (MS) varies widely among individuals. Understanding the determinants of this heterogeneity will help clinicians optimize the management of MS. The aim of this study was to investigate the association between latitude of residence, UV B radiation (UVB) exposure, and the severity of MS., Methods: This observational study used the MSBase registry data. The included patients met the 2005 or 2010 McDonald diagnostic criteria for MS and had a minimum dataset recorded in the registry (date of birth, sex, clinic location, date of MS symptom onset, disease phenotype at baseline and censoring, and ≥1 Expanded Disability Status Scale score recorded). The latitude of each study center and cumulative annualized UVB dose at study center (calculated from National Aeronautics and Space Administration's Total Ozone Mapping Spectrometer) at ages 6 and 18 years and the year of disability assessment were calculated. Disease severity was quantified with Multiple Sclerosis Severity Score (MSSS). Quadratic regression was used to model the associations between latitude, UVB, and MSSS., Results: The 46,128 patients who contributed 453,208 visits and a cumulative follow-up of 351,196 patient-years (70% women, mean age 39.2 ± 12 years, resident between latitudes 19°35' and 56°16') were included in this study. Latitude showed a nonlinear association with MS severity. In latitudes <40°, more severe disease was associated with higher latitudes (β = 0.08, 95% CI 0.04-0.12). For example, this translates into a mean difference of 1.3 points of MSSS between patients living in Madrid and Copenhagen. No such association was observed in latitudes <40° (β = -0.02, 95% CI -0.06 to 0.03). The overall disability accrual was faster in those with a lower level of estimated UVB exposure before the age of 6 years (β = - 0.5, 95% CI -0.6 to 0.4) and 18 years (β = - 0.6, 95% CI -0.7 to 0.4), as well as with lower lifetime UVB exposure at the time of disability assessment (β = -1.0, 95% CI -1.1 to 0.9)., Discussion: In temperate zones, MS severity is associated with latitude. This association is mainly, but not exclusively, driven by UVB exposure contributing to both MS susceptibility and severity., (© 2022 American Academy of Neurology.)

Importance: Multiple sclerosis can also affect children. Approximately 3-10% of patients develop multiple sclerosis before the age of 16., Objective: The aim of this analysis is to describe the characteristics of pediatric patients with multiple sclerosis who started their treatment with disease-modifying drugs in 2013-2020, with data obtained from the Czech National Registry of patients with multiple sclerosis., Design and Setting: A method of retrospective analysis conducted with 134 pediatric patients with multiple sclerosis was used., Results: The findings reveal that the mean age at the date of the introduction of the first disease-modifying drugs treatment is 15.89 years, and gender does not play any role. In addition, moderate (51.6%) and mild (45.2%) relapses are predominant in these young patients. Seventy five percent of patients will not experience a confirmed progression of the expanded disability status scale within 54.7 months from starting the treatment. Furthermore, the results confirm that the first-choice treatment is interferon beta-a and glatiramer acetate, which is common for adult patients. However, some factors, such as a low efficacy or a lack of tolerance may impact on treatment discontinuation in children., Conclusion: More research should be performed on novel disease-modifying drugs for this target group., Competing Interests: MVac was employed by KZ a.s., Hospital Teplice. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Vališ, Pavelek, Novotný, Klímová, Šarláková, Halúsková, Peterka, Štětkárová, Štourač, Mareš, Hradílek, Ampapa, Vachová, Recmanová and Meluzínová.)

Background: A special care of MS women planning a pregnancy is highly demanding especially in the terms of disease modifying treatment (DMD) decisions and counselling regarding periods of conception, pregnancy and postpartum period., Objective: To provide data about impact of pregnancy, delivery or miscarriage/artificial abortion on MS disease course in Czech women with MS based on analysis of retrospective data from the Czech national registry ReMuS., Methods: The analysis focused on women with MS with at least one record of pregnancy in the registry. Clinical data (EDSS, relapses) were collected prior to conception, during pregnancy and after delivery or miscarriage/artificial abortion. These data were analysed according to baseline characteristics of DMD treatment prior to conception and according to breastfeeding status., Results: A total of 1 533 pregnancies were analysed from the period of 2013 until 31st December 2019. The occurrence of relapses and worse EDSS was significantly related to the treatment with escalation therapy prior to conception. Relapses were significantly more frequent in women who breastfed less than 3 months than in women who breastfed more than 3 months or did not breastfeed at all. Patients treated with either fingolimod or natalizumab prior to pregnancy were significantly more likely to develop relapses during pregnancy., Conclusion: Pregnancy and postpartum period were generally safe for Czech women with MS. Better disease outcomes were observed in those who had been treated with first line injectable DMDs prior to conception and those who either breastfed more than 3 months or did not breastfeed at all. We confirmed the assumption of rebound phenomenon of MS after discontinuation of treatment due to planned pregnancy both for fingolimod and natalizumab., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Background: When the novel coronavirus disease 2019 (COVID-19) appeared, concerns about its course in patients with multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD) arose. This study aimed to evaluate the incidence, severity and risk factors of the more severe COVID-19 course among MS and NMOSD patients., Methods: From March 1, 2020, to February 28, 2021, 12 MS centres, representing 70% of the Czech MS and NMOSD population, reported laboratory-confirmed COVID-19 cases via the Czech nationwide register of MS and NMOSD patients (ReMuS). The main outcome was COVID-19 severity assessed on an 8-point scale with a cut-off at 4 (radiologically confirmed pneumonia) according to the World Health Organisation´s (WHO) COVID-19 severity assessment., Results: We identified 958 MS and 13 NMOSD patients, 50 MS and 4 NMOSD patients had pneumonia, 3 MS and 2 NMOSD patients died. The incidence of COVID-19 among patients with MS seems to be similar to the general Czech population. A multivariate logistic regression determined that higher body mass index (BMI [OR 1.07, 95% CI, 1.00-1.14]), older age (OR per 10 years 2.01, 95% CI, 1.41-2.91), high-dose glucocorticoid treatment during the 2 months before COVID-19 onset (OR 2.83, 95% CI, 0.10-7.48) and anti-CD20 therapy (OR 7.04, 95% CI, 3.10-15.87) were independent variables associated with pneumonia in MS patients. Increase odds of pneumonia in anti-CD20 treated MS patients compared to patients with other disease-modifying therapy (same age, sex, BMI, high-dose glucocorticoid treatment during the 2 months before COVID-19 onset, presence of pulmonary comorbidity) were confirmed by propensity score matching (OR 8.90, 95% CI, 3.04-33.24). Reports on COVID-19 infection in patients with NMOSD are scarce, however, data available up to now suggest a high risk of a more severe COVID-19 course as well as a higher mortality rate among NMOSD patients. In our cohort, 4 NMOSD patients (30.77%) had the more severe COVID-19 course and 2 patients (15.39%) died., Conclusion: The majority of MS patients had a mild COVID-19 course contrary to NMOSD patients, however, higher BMI and age, anti-CD20 therapy and high-dose glucocorticoid treatment during the 2 months before COVID-19 onset were associated with pneumonia. Based on this study, we have already started an early administration of anti-SARS-CoV-2 monoclonal antibodies and preferential vaccination in the risk group of patients., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Objective: To investigate pregnancy-related disease activity in a contemporary multiple sclerosis (MS) cohort., Methods: Using data from the MSBase Registry, we included pregnancies conceived after 31 Dec 2010 from women with relapsing-remitting MS or clinically isolated syndrome. Predictors of intrapartum relapse, and postpartum relapse and disability progression were determined by clustered logistic regression or Cox regression analyses., Results: We included 1998 pregnancies from 1619 women with MS. Preconception annualized relapse rate (ARR) was 0.29 (95% CI 0.27-0.32), fell to 0.19 (0.14-0.24) in third trimester, and increased to 0.59 (0.51-0.67) in early postpartum. Among women who used fingolimod or natalizumab, ARR before pregnancy was 0.37 (0.28-0.49) and 0.29 (0.22-0.37), respectively, and increased during pregnancy. Intrapartum ARR decreased with preconception dimethyl fumarate use. ARR spiked after delivery across all DMT groups. Natalizumab continuation into pregnancy reduced the odds of relapse during pregnancy (OR 0.76 per month [0.60-0.95], p=0.017). DMT re-initiation with natalizumab protected against postpartum relapse (HR 0.11 [0.04-0.32], p<0.0001). Breastfeeding women were less likely to relapse (HR 0.61 [0.41-0.91], p=0.016). 5.6% of pregnancies were followed by confirmed disability progression, predicted by higher relapse activity in pregnancy and postpartum., Conclusion: Intrapartum and postpartum relapse probabilities increased among women with MS after natalizumab or fingolimod cessation. In women considered to be at high relapse risk, use of natalizumab before pregnancy and continued up to 34 weeks gestation, with early re-initiation after delivery is an effective option to minimize relapse risks. Strategies of DMT use have to be balanced against potential fetal/neonatal complications., (© 2021 American Academy of Neurology.)

Background: Cerebellar and brainstem symptoms are common in early stages of multiple sclerosis (MS) yet their prognostic values remain unclear., Objective: The aim of this study was to investigate long-term disability outcomes in patients with early cerebellar and brainstem symptoms., Methods: This study used data from MSBase registry. Patients with early cerebellar/brainstem presentations were identified as those with cerebellar/brainstem relapse(s) or functional system score ⩾ 2 in the initial 2 years. Early pyramidal presentation was chosen as a comparator. Andersen-Gill models were used to compare cumulative hazards of (1) disability progression events and (2) relapses between patients with and without early cerebellar/brainstem symptoms. Mixed effect models were used to estimate the associations between early cerebellar/brainstem presentations and expanded disability status scale (EDSS) scores., Results: The study cohort consisted of 10,513 eligible patients, including 2723 and 3915 patients with early cerebellar and brainstem symptoms, respectively. Early cerebellar presentation was associated with greater hazard of progression events (HR = 1.37, p  < 0.001) and EDSS (β = 0.16, p  < 0.001). Patients with early brainstem symptoms had lower hazard of progression events (HR = 0.89, p  = 0.01) and EDSS (β = -0.06, p  < 0.001). Neither presentation was associated with changes in relapse risk., Conclusion: Early cerebellar presentation is associated with unfavourable outcomes, while early brainstem presentation is associated with favourable prognosis. These presentations may be used as MS prognostic markers and guide therapeutic approach.

Objective: To test the hypothesis that immunotherapy prevents long-term disability in relapsing-remitting multiple sclerosis (MS), we modeled disability outcomes in 14,717 patients., Methods: We studied patients from MSBase followed for ≥1 year, with ≥3 visits, ≥1 visit per year, and exposed to MS therapy, and a subset of patients with ≥15-year follow-up. Marginal structural models were used to compare the cumulative hazards of 12-month confirmed increase and decrease in disability, Expanded Disability Status Scale (EDSS) step 6, and the incidence of relapses between treated and untreated periods. Marginal structural models were continuously readjusted for patient age, sex, pregnancy, date, disease course, time from first symptom, prior relapse history, disability, and MRI activity., Results: A total of 14,717 patients were studied. During the treated periods, patients were less likely to experience relapses (hazard ratio 0.60, 95% confidence interval [CI] 0.43-0.82, p = 0.0016), worsening of disability (0.56, 0.38-0.82, p = 0.0026), and progress to EDSS step 6 (0.33, 0.19-0.59, p = 0.00019). Among 1,085 patients with ≥15-year follow-up, the treated patients were less likely to experience relapses (0.59, 0.50-0.70, p = 10 -9 ) and worsening of disability (0.81, 0.67-0.99, p = 0.043)., Conclusion: Continued treatment with MS immunotherapies reduces disability accrual by 19%-44% (95% CI 1%-62%), the risk of need of a walking aid by 67% (95% CI 41%-81%), and the frequency of relapses by 40-41% (95% CI 18%-57%) over 15 years. This study provides evidence that disease-modifying therapies are effective in improving disability outcomes in relapsing-remitting MS over the long term., Classification of Evidence: This study provides Class IV evidence that, for patients with relapsing-remitting MS, long-term exposure to immunotherapy prevents neurologic disability., (© 2020 American Academy of Neurology.)

Background: Multiple sclerosis (MS) is a chronic inflammatory and neurodegenerative disease of the central nervous system. Well-established drugs used for MS patients after the first demyelinating event in the Czech Republic include glatiramer acetate (GA), interferon beta-1a (IFNβ-1a), IFN beta-1b (IFNβ-1b), peginterferon beta-1a (peg-IFNβ-1a), and teriflunomide. Objective: The objective of this observational study was to compare the effectiveness of the abovementioned drugs in patients with MS who initiated their therapy after the first demyelinating event. Patients were followed for up to 2 years in real clinical practice in the Czech Republic. Methods: A total of 1,654 MS patients treated after the first demyelinating event and followed up for 2 years were enrolled. Evaluation parameters (endpoints) included the annualized relapse rate (ARR), time to next relapse, change in the Expanded Disability Status Scale (EDSS) score, and time of confirmed disease progression (CDP). When patients ended the therapy before the observational period, the reason for ending the therapy among different treatments was compared. Results: No significant difference was found among the groups of patients treated with IFNβ-1a/1b, GA, or teriflunomide for the following parameters: time to the first relapse, change in the EDSS score, and the proportion of patients with CDP. Compared to IFNβ-1a (44 mcg), a significant increase in the percentage of relapse-free patients was found for GA, but this treatment effect was not confirmed by the validation analysis. Compared to the other drugs, there was a significant difference in the reasons for terminating GA therapy. Conclusion: Small differences were found among GA, IFNβ and teriflunomide therapies, with no significant impact on the final outcome after 2 years. Therefore, in clinical practice, we recommend choosing the drug based on individual potential risk from long-term therapy and on patient preferences and clinical characteristics., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Pavelek, Sobíšek, Šarláková, Potužník, Peterka, Štětkárová, Štourač, Mareš, Hradílek, Ampapa, Grünermelová, Vachová, Recmanová, Angelucci, Halúsková and Vališ.)

Background: The risk factors for conversion from relapsing-remitting to secondary progressive multiple sclerosis remain highly contested., Objective: The aim of this study was to determine the demographic, clinical and paraclinical features that influence the risk of conversion to secondary progressive multiple sclerosis., Methods: Patients with adult-onset relapsing-remitting multiple sclerosis and at least four recorded disability scores were selected from MSBase, a global observational cohort. The risk of conversion to objectively defined secondary progressive multiple sclerosis was evaluated at multiple time points per patient using multivariable marginal Cox regression models. Sensitivity analyses were performed., Results: A total of 15,717 patients were included in the primary analysis. Older age (hazard ratio (HR) = 1.02, p  < 0.001), longer disease duration (HR = 1.01, p  = 0.038), a higher Expanded Disability Status Scale score (HR = 1.30, p  < 0.001), more rapid disability trajectory (HR = 2.82, p  < 0.001) and greater number of relapses in the previous year (HR = 1.07, p  = 0.010) were independently associated with an increased risk of secondary progressive multiple sclerosis. Improving disability (HR = 0.62, p  = 0.039) and disease-modifying therapy exposure (HR = 0.71, p  = 0.007) were associated with a lower risk. Recent cerebral magnetic resonance imaging activity, evidence of spinal cord lesions and oligoclonal bands in the cerebrospinal fluid were not associated with the risk of conversion., Conclusion: Risk of secondary progressive multiple sclerosis increases with age, duration of illness and worsening disability and decreases with improving disability. Therapy may delay the onset of secondary progression.

Objective: Oral immunotherapies have become a standard treatment in relapsing-remitting multiple sclerosis. Direct comparison of their effect on relapse and disability is needed., Methods: We identified all patients with relapsing-remitting multiple sclerosis treated with teriflunomide, dimethyl fumarate or fingolimod, with minimum 3-month treatment persistence and disability follow-up in the global MSBase cohort study. Patients were matched using propensity scores. Three pairwise analyses compared annualised relapse rates and hazards of disability accumulation, disability improvement and treatment discontinuation (analysed with negative binomial models and weighted conditional survival models, with pairwise censoring)., Results: The eligible cohorts consisted of 614 (teriflunomide), 782 (dimethyl fumarate) or 2332 (fingolimod) patients, followed over the median of 2.5 years. Annualised relapse rates were lower on fingolimod compared with teriflunomide (0.18 vs 0.24; p=0.05) and dimethyl fumarate (0.20 vs 0.26; p=0.01) and similar on dimethyl fumarate and teriflunomide (0.19 vs 0.22; p=0.55). No differences in disability accumulation (p≥0.59) or improvement (p≥0.14) were found between the therapies. In patients with ≥3-month treatment persistence, subsequent discontinuations were less likely on fingolimod than teriflunomide and dimethyl fumarate (p<0.001). Discontinuation rates on teriflunomide and dimethyl fumarate were similar (p=0.68)., Conclusion: The effect of fingolimod on relapse frequency was superior to teriflunomide and dimethyl fumarate. The effect of the three oral therapies on disability outcomes was similar during the initial 2.5 years on treatment. Persistence on fingolimod was superior to the two comparator drugs., Competing Interests: Competing interests: TK served on scientific advisory boards for Roche, Genzyme-Sanofi, Novartis, Merck and Biogen, steering committee for Brain Atrophy Initiative by Genzyme, received conference travel support and/or speaker honoraria from WebMD Global, Novartis, Biogen, Genzyme-Sanofi, Teva, BioCSL and Merck and received research support from Biogen. EKH received speaker honoraria and consultant fees from Actelion, Biogen, Celgene, Merck, Novartis, Roche, Sanofi and Teva, and support for research activities from Czech Ministry of Education (project PROGRES Q27/LF1). DH received speaker honoraria and consulting fees from Biogen, Merck, Teva, Roche, Sanofi Genzyme and Novartis, as well as support for research activities from Biogen and Czech Ministry of Education (project PROGRES Q27/LF1). GI received speaking honoraria from Biogen, Novartis, Sanofi, Merck, Roche, Almirall and Teva. MG received consulting fees from Teva Canada Innovation, Biogen, Novartis and Genzyme Sanofi; lecture payments from Teva Canada Innovation, Novartis and EMD. He has also received a research grant from Canadian Institutes of Health Research. PD served on editorial boards and has been supported to attend meetings by EMD, Biogen, Novartis, Genzyme and TEVA Neuroscience. He holds grants from the CIHR and the MS Society of Canada and has received funding for investigator-initiated trials from Biogen, Novartis and Genzyme. PG is a Merck, Novartis, Teva-Neuroscience, Biogen and Genzyme advisory board member, consultant for Merck, received payments for lectures by Merck, Teva-Neuroscience and Canadian Multiple Sclerosis Society, and received grants for travel from Teva-Neuroscience and Novartis. AL served as a Bayer, Biogen, Merck, Novartis, Roche, Sanofi/Genzyme and Teva Advisory Board Member. She received congress and travel/accommodation expense compensations and speaker honoraria from Bayer, Biogen, Merck, Novartis, Sanofi/Genzyme, Teva and Fondazione Italiana Sclerosi Multipla (FISM). Her institutions received research grants from Novartis. LK received research support from Acorda, Actelion, Allozyne, BaroFold, Bayer Health Care, Bayer Schering, Bayhill Therapeutics, Biogen, Elan, European Union, Genmab, Gianni Rubatto Foundation, GlaxoSmithKline, Glenmark, MediciNova, Merck, Novartis, Novartis Research Foundation, Roche, Roche Research Foundation, Sanofi-Aventis, Santhera, Swiss MS Society, Swiss National Research Foundation, Teva Neuroscience, UCB and Wyeth. JK received consulting fees from Novartis, Protagen; speaker fees from the Swiss MS Society, Biogen, Novartis, Roche, Genzyme; travel expenses from Merck Serono, Novartis; grants from ECTRIMS Research Fellowship Programme, University of Basel, Swiss MS Society, Swiss National Research Foundation, Bayer (Schweiz), Genzyme and Novartis. MT received travel grants from Novartis, Bayer Schering, Merck and Teva; has participated in clinical trials by Sanofi Aventis, Roche and Novartis. JLS accepted travel compensation from Novartis, Biogen and Merck. Her institution receives the honoraria for talks and advisory board commitment from Bayer Health Care, Biogen, Genzyme Sanofi, Merck, Novartis and Teva; has been involved in clinical trials with Biogen, Novartis and Teva. CB received conference travel support from Biogen, Novartis, Bayer Schering, Merck and Teva; has participated in clinical trials by Sanofi Aventis, Roche and Novartis. FGM received honoraria or research funding from Biogen, Genzyme, Novartis, Teva Neurosciences, Mitsubishi and ONO Pharmaceuticals. JP accepted travel compensation from Novartis, Biogen, Genzyme and Teva and speaking honoraria from Biogen, Novartis, Genzyme and Teva. PS served on scientific advisory boards for Biogen Idec and TEVA; she has received funding for travel and speaker honoraria from Biogen Idec, Merck, Teva, Sanofi Genzyme, Novartis and Bayer and research grants for her institution from Bayer, Biogen, Merck, Novartis, Sanofi and Teva. DF received travel grants and/or speaker honoraria from Merck, TEVA, Novartis, Biogen and Sanofi Genzyme. FG received an institutional research grant from Biogen and Sanofi Genzyme; served on scientific advisory boards for Biogen, Novartis, Merck, Sanofi Genzyme and Roche; received funding for travel and speaker honoraria from Biogen, Merck and Sanofi-Aventis. MT received speaker honoraria from Biogen-Idec, Bayer Schering, Sanofi Aventis, Merck, Teva, Novartis and Almirall; has received research grants for her Institution from Biogen-Idec, Merck and Novartis. RB received speaker honoraria from Bayer Schering, Biogen, Genzyme, Merck, Novartis, Sanofi-Aventis and Teva; research grants from Bayer Schering, Biogen, Merck, Novartis, Sanofi-Aventis and Teva; congress and travel/accommodation expense compensations by Almirall, Bayer Schering, Biogen, Genzyme, Merck, Novartis, Sanofi-Aventis and Teva. EP served on scientific advisory boards for Merck, Genzyme and Biogen; he has received honoraria and travel grants from Sanofi Aventis, Novartis, Biogen, Merck, Genzyme and Teva; he has received travel grants and equipment from 'Associazione Marchigiana Sclerosi Multipla e altre malattie neurologiche'. VVP received travel grants from Biogen, Bayer Schering, Genzyme, Merck, Teva and Novartis Pharma. His institution receives honoraria for consultancy and lectures from Biogen, Bayer Schering, Genzyme, Merck, Roche, Teva and Novartis Pharma as well as research grants from Novartis Pharma and Bayer Schering. BVW received research and travel grants, honoraria for MS-Expert advisor and speaker fees from Bayer Schering, Biogen, Sanofi Genzyme, Merck, Novartis, Roche and Teva. CS served on scientific advisory boards for Merck, Genzyme, Almirall and Biogen; received honoraria and travel grants from Sanofi Aventis, Novartis, Biogen, Merck, Genzyme and Teva. CRT received research funding, compensation for travel or speaker honoraria from Biogen, Novartis, Genzyme and Almirall. MS has participated in, but not received honoraria for, advisory board activity for Biogen, Merck, Bayer Schering, Sanofi Aventis and Novartis. RA received honoraria as a speaker and for serving on scientific advisory boards from Bayer, Biogen, GSK, Merck, Novartis, Roche and Sanofi Genzyme. DLS received honoraria as a consultant on scientific advisory boards by Bayer Schering, Novartis and Sanofi-Aventis and compensation for travel from Novartis, Biogen, Sanofi Aventis, Teva and Merck. JLSM accepted travel compensation from Novartis and Biogen, speaking honoraria from Biogen, Novartis, Sanofi, Merck, Almirall, Bayer and Teva and has participated in a clinical trial by Biogen. RA received conference travel support from Novartis, Teva, Biogen, Bayer and Merck and has participated in a clinical trial by Biogen, Novartis, Teva and Actelion. SH received honoraria and consulting fees from Merck, Novartis, Bayer Schering and Sanofi, and travel grants from Novartis, Biogen Idec and Bayer Schering. Ricardo Fernandez Bolaños received speaking honoraria from Biogen, Novartis, Merck and Teva. VJ received conference travel support from Teva, Novartis and Merck, and speaker honoraria from Biogen. TS received honoraria for consultancy, funding for travel and compensation for serving on scientific advisory boards from Biogen and speaker honoraria from Novartis. HB served on scientific advisory boards for Biogen, Novartis and Sanofi-Aventis and has received conference travel support from Novartis, Biogen and Sanofi Aventis. He serves on steering committees for trials conducted by Biogen and Novartis, and has received research support from Merck, Novartis and Biogen., (© Author(s) (or their employer(s)) 2019. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Exposure to disease-modifying therapy (DMT) during early pregnancy in women with relapsing-remitting MS (RRMS) may be increasing., Objective: To retrospectively determine incidence of pregnancy, DMT exposure and pregnancy outcomes in women with RRMS., Methods: We identified all women with RRMS aged 15-45 years in the MSBase Registry between 2005-2016. Annualised pregnancy incidence rates were calculated using Poisson regression models. DMT exposures and pregnancy outcomes were assessed., Results: Of 9,098 women meeting inclusion criteria, 1,178 (13%) women recorded 1,521 pregnancies. The annualised incidence rate of pregnancy was 0.042 (95% CI 0.040, 0.045). A total of 635 (42%) reported pregnancies were conceived on DMT, increasing from 27% in 2006 to 62% in 2016. The median duration of DMT exposure during pregnancy was 30 days (IQR: 9, 50). There were a higher number of induced abortions on FDA pregnancy class C/D drugs compared with pregnancy class B and no DMT (p = 0.010); but no differences in spontaneous abortions, term or preterm births., Conclusions: We report low pregnancy incidence rates, with increasing number of pregnancies conceived on DMT over the past 12-years. The median duration of DMT exposure in pregnancy was relatively short at one month., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Timely initiation of effective therapy is crucial for preventing disability in multiple sclerosis; however, treatment response varies greatly among patients. Comprehensive predictive models of individual treatment response are lacking. Our aims were: (i) to develop predictive algorithms for individual treatment response using demographic, clinical and paraclinical predictors in patients with multiple sclerosis; and (ii) to evaluate accuracy, and internal and external validity of these algorithms. This study evaluated 27 demographic, clinical and paraclinical predictors of individual response to seven disease-modifying therapies in MSBase, a large global cohort study. Treatment response was analysed separately for disability progression, disability regression, relapse frequency, conversion to secondary progressive disease, change in the cumulative disease burden, and the probability of treatment discontinuation. Multivariable survival and generalized linear models were used, together with the principal component analysis to reduce model dimensionality and prevent overparameterization. Accuracy of the individual prediction was tested and its internal validity was evaluated in a separate, non-overlapping cohort. External validity was evaluated in a geographically distinct cohort, the Swedish Multiple Sclerosis Registry. In the training cohort (n = 8513), the most prominent modifiers of treatment response comprised age, disease duration, disease course, previous relapse activity, disability, predominant relapse phenotype and previous therapy. Importantly, the magnitude and direction of the associations varied among therapies and disease outcomes. Higher probability of disability progression during treatment with injectable therapies was predominantly associated with a greater disability at treatment start and the previous therapy. For fingolimod, natalizumab or mitoxantrone, it was mainly associated with lower pretreatment relapse activity. The probability of disability regression was predominantly associated with pre-baseline disability, therapy and relapse activity. Relapse incidence was associated with pretreatment relapse activity, age and relapsing disease course, with the strength of these associations varying among therapies. Accuracy and internal validity (n = 1196) of the resulting predictive models was high (>80%) for relapse incidence during the first year and for disability outcomes, moderate for relapse incidence in Years 2-4 and for the change in the cumulative disease burden, and low for conversion to secondary progressive disease and treatment discontinuation. External validation showed similar results, demonstrating high external validity for disability and relapse outcomes, moderate external validity for cumulative disease burden and low external validity for conversion to secondary progressive disease and treatment discontinuation. We conclude that demographic, clinical and paraclinical information helps predict individual response to disease-modifying therapies at the time of their commencement., (© The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Background: Alemtuzumab, an anti-CD52 antibody, is proven to be more efficacious than interferon beta-1a in the treatment of relapsing-remitting multiple sclerosis, but its efficacy relative to more potent immunotherapies is unknown. We compared the effectiveness of alemtuzumab with natalizumab, fingolimod, and interferon beta in patients with relapsing-remitting multiple sclerosis treated for up to 5 years., Methods: In this international cohort study, we used data from propensity-matched patients with relapsing-remitting multiple sclerosis from the MSBase and six other cohorts. Longitudinal clinical data were obtained from 71 MSBase centres in 21 countries and from six non-MSBase centres in the UK and Germany between Nov 1, 2015, and June 30, 2016. Key inclusion criteria were a diagnosis of definite relapsing-remitting multiple sclerosis, exposure to one of the study therapies (alemtuzumab, interferon beta, fingolimod, or natalizumab), age 65 years or younger, Expanded Disability Status Scale (EDSS) score 6·5 or lower, and no more than 10 years since the first multiple sclerosis symptom. The primary endpoint was annualised relapse rate. The secondary endpoints were cumulative hazards of relapses, disability accumulation, and disability improvement events. We compared relapse rates with negative binomial models, and estimated cumulative hazards with conditional proportional hazards models., Findings: Patients were treated between Aug 1, 1994, and June 30, 2016. The cohorts consisted of 189 patients given alemtuzumab, 2155 patients given interferon beta, 828 patients given fingolimod, and 1160 patients given natalizumab. Alemtuzumab was associated with a lower annualised relapse rate than interferon beta (0·19 [95% CI 0·14-0·23] vs 0·53 [0·46-0·61], p<0·0001) and fingolimod (0·15 [0·10-0·20] vs 0·34 [0·26-0·41], p<0·0001), and was associated with a similar annualised relapse rate as natalizumab (0·20 [0·14-0·26] vs 0·19 [0·15-0·23], p=0·78). For the disability outcomes, alemtuzumab was associated with similar probabilities of disability accumulation as interferon beta (hazard ratio [HR] 0·66 [95% CI 0·36-1·22], p=0·37), fingolimod (1·27 [0·60-2·70], p=0·67), and natalizumab (0·81 [0·47-1·39], p=0·60). Alemtuzumab was associated with similar probabilities of disability improvement as interferon beta (0·98 [0·65-1·49], p=0·93) and fingolimod (0·50 [0·25-1·01], p=0·18), and a lower probability of disability improvement than natalizumab (0·35 [0·20-0·59], p=0·0006)., Interpretation: Alemtuzumab and natalizumab seem to have similar effects on annualised relapse rates in relapsing-remitting multiple sclerosis. Alemtuzumab seems superior to fingolimod and interferon beta in mitigating relapse activity. Natalizumab seems superior to alemtuzumab in enabling recovery from disability. Both natalizumab and alemtuzumab seem highly effective and viable immunotherapies for multiple sclerosis. Treatment decisions between alemtuzumab and natalizumab should be primarily governed by their safety profiles., Funding: National Health and Medical Research Council, and the University of Melbourne., (Copyright © 2017 Elsevier Ltd. All rights reserved.)