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Previous research discovered a protective effect of higher conscientiousness against a 3-year deterioration in employment status in persons with multiple sclerosis (pwMS). To replicate these findings, we used data from a multicentre prospective cohort study where 145 employed pwMS completed questionnaires, neurological and neuropsychological examinations at baseline and after 3 years. A 3-year deterioration in employment status was reported in 31.0%. We observed no differences in personality, demographics or clinical characteristics between pwMS with deteriorated or stable employment status. These null findings may be partly explained by the classification of deteriorated employment status, which does not reflect Dutch labour conditions. [ABSTRACT FROM AUTHOR]

Background: Spinal cord lesions in multiple sclerosis (MS) have considerable impact on disability. High-efficacy disease-modifying treatments (hDMTs) are associated with greater reduction of relapses and new brain lesions compared to low-efficacy treatments (lDMTs). Knowledge on the impact of DMTs on cord lesion formation is limited as these outcome measures were not included in MS treatment trials. This study aims to investigate whether hDMTs reduce the formation of cord lesions more effectively than lDMTs., Methods: Patients with relapse-onset MS, a cord magnetic resonance imaging (MRI) within 6 months before/after initiation of their first DMT and ≥1 cord MRI at follow-up (interval > 6 months) were extracted from the MSBase registry (ACTRN12605000455662). Patients treated with hDMTs ≥90% or lDMTs ≥90% of follow-up duration were considered the hDMT and lDMT groups, respectively. Matching was performed using propensity scores. Cox proportional hazards models were used to estimate the hazards of new cord lesions, brain lesions and relapses., Results: Ninety-four and 783 satisfied hDMT and lDMT group criteria, respectively. Seventy-seven hDMT patients were matched to 184 lDMT patients. In the hDMT group there was no evidence of reduction of new cord lesions (hazard ratio [HR] 0.99 [95% CI 0.51, 1.92], p = 0.97), while there were fewer new brain lesions (HR 0.22 [95% CI 0.10, 0.49], p < 0.001) and fewer relapses (HR 0.45 [95% CI 0.28, 0.72], p = 0.004)., Conclusion: A potential discrepancy exists in the effect of hDMTs over lDMTs in preventing spinal cord lesions versus brain lesions and relapses. While hDMTs provided a significant reduction for the latter when compared to lDMTs, there was no significant reduction in new spinal cord lesions., (© 2024. The Author(s).)

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&#95;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.)

Purpose: To investigate longitudinal relationships between employment status and disease-related, (neuro)psychological, and work-related factors in people with multiple sclerosis (MS)., Methods: 170 employed people with MS underwent yearly neurological and neuropsychological examinations to assess MS-related disability and cognitive functioning. Additionally, they completed yearly questionnaires assessing depression, anxiety, fatigue, cognitive complaints, workplace support and coping. Multilevel models for change were fitted to examine progression of these factors over three years, and to assess possible relationships with change in employment status., Results: People with a deteriorated employment status after three years reported more depression ( p= 0.009), a higher impact of fatigue ( p< 0.001), more cognitive complaints ( p< 0.001) and less workplace support ( p= 0.001) at baseline than people with a stable employment status. There were no differences in progression over time of the examined variables between people with a stable or deteriorated employment status., Conclusion: More depression, a higher impact of fatigue, more cognitive complaints and less workplace support are predictive of a deteriorated employment status after three years in individuals with MS. How these factors progress over time is not different between those with a stable or deteriorated employment. MS-related disability, anxiety, objective cognition and coping were not related to a deterioration in employment status., Competing Interests: E.E.A. van Egmond, K. van der Hiele, M.J. de Rooij, D.A.M. van Gorp, J.J.L. van der Klink, M.F. Reneman, E.A.C. Beenakker, S.T.F.M. Frequin, K. de Gans, O.H.H. Gerlach, J.P. Mostert, and H.A.M. Middelkoop declare no conflict of interestP.J. Jongen received honoraria from Bayer Netherlands and Orikami Personalized Health Care for consultancy activities and is chairman of the MSmonitor Foundation.L.H. Visser received a research grant for the multicentre BIA study from Merck, received consultancy fees from Merck, Novartis and JanssenJ.J.J. van Eijk received consultancy fees and honoraria for lectures from Merck, Biogen, Novartis, Sanofi, Janssen and RocheE. Hoitsma received honoraria for lectures and advisory boards from Bayer, Biogen, Roche, Sanofi Genzyme, Merck Serono, Novartis and Teva.W.I.M. Verhagen received consultancy fees from Merck and Biogen, (© 2024 The Authors.)

A disparity exists between spinal cord and brain involvement in multiple sclerosis (MS), each independently contributing to disability. Underlying differences between brain and cord are not just anatomical in nature (volume, white/grey matter organization, vascularization), but also in barrier functions (differences in function and composition of the blood-spinal cord barrier compared to blood-brain barrier) and possibly in repair mechanisms. Also, immunological phenotypes seem to influence localization of inflammatory activity. Whereas the brain has gained a lot of attention in MS research, the spinal cord lags behind. Advanced imaging techniques and biomarkers are improving and providing us with tools to uncover the mechanisms of spinal cord pathology in MS. In the present review, we elaborate on the underlying anatomical and physiological factors driving differences between brain and cord involvement in MS and review current literature on pathophysiology of spinal cord involvement in MS and the observed differences to brain involvement., Competing Interests: Declaration of Competing Interest DK, AP and OG have nothing to disclose; RH received institutional research grants and fees for lectures and advisory boards from Biogen, Merck and Genzyme-Sanofi., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

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.

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).)

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: Whether progression independent of relapse activity (PIRA) heralds earlier onset of secondary progressive multiple sclerosis (SPMS) and more rapid accumulation of disability during SPMS remains to be determined. We investigated the association between early PIRA, relapse-associated worsening (RAW) of disability and time to SPMS, subsequent disability progression and their response to therapy., Methods: This observational cohort study included patients with relapsing-remitting multiple sclerosis (RRMS) from the MSBase international registry across 146 centres and 39 countries. Associations between the number of PIRA and RAW during early multiple sclerosis (MS) (the initial 5 years of MS onset) were analysed with respect to: time to SPMS using Cox proportional hazards models adjusted for disease characteristics; and disability progression during SPMS, calculated as the change of Multiple Sclerosis Severity Scores over time, using multivariable linear regression., Results: 10 692 patients met the inclusion criteria: 3125 (29%) were men and the mean MS onset age was 32.2 years. A higher number of early PIRA (HR=1.50, 95% CI 1.28 to 1.76, p<0.001) and RAW (HR=2.53, 95% CI 2.25 to 2.85, p<0.001) signalled a higher risk of SPMS. A higher proportion of early disease-modifying therapy exposure (per 10%) reduced the effect of early RAW (HR=0.94, 95% CI 0.89 to 1.00, p=0.041) but not PIRA (HR=0.97, 95% CI 0.91 to 1.05, p=0.49) on SPMS risk. No association between early PIRA/RAW and disability progression during SPMS was found., Conclusions: Early disability increase during RRMS is associated with a greater risk of SPMS but not the rate of disability progression during SPMS. The deterioration associated with early relapses represents a potentially treatable risk factor of SPMS., Trial Registration Number: Australian New Zealand Clinical Trials Registry (ACTRN12605000455662)., Competing Interests: Competing interests: WD has nothing to declare. SS has nothing to declare. FP 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. 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. AP has nothing to declare. 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. MO has nothing to declare. AL has received personal compensation for consulting, serving on a scientific advisory board, speaking or other activities from Biogen, Merck Serono, Mylan, Novartis, Roche, Sanofi/Genzyme, Teva. Her institutions have receved research grants from Novartis [last 4 yrs]. SO has nothing to declare. OG has nothing to declare. CB received conference travel support from Biogen, Novartis, Bayer-Schering, Merck and Teva; has participated in clinical trials by Sanofi Aventis, Roche and Novartis. PG 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. MT received travel grants from Novartis, Bayer-Schering, Merck and Teva; has participated in clinical trials by Sanofi Aventis, Roche and Novartis. MPA received honoraria as consultant on scientific advisory boards by Biogen, Bayer-Schering, Merck, Teva and Sanofi-Aventis; has received research grants by Biogen, Bayer-Schering, Merck, Teva and Novartis. DS 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. CR-T received research funding, compensation for travel or speaker honoraria from Biogen, Novartis, Genzyme and Almirall. DM received speaker honoraria for Advisory Board and travel grants from Almirall, Biogen, Merck, Novartis, Roche, Sanofi-Genzyme, and Teva. EC has nothing to declare. TK served on scientific advisory boards for BMS, Roche, 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. KB received honoraria and consulting fees from Biogen, Teva, Novartis, Genzyme-Sanofi, Roche, Merck, CSL and Grifols. OS has nothing to declare. AvdW has nothing to declare. HB Institution (Monash university) has received compensation for consulting, talks, advisory/steering board activities from Biogen, Merck, Novartis, Genzyme, Alfred Health; research support from Novartis, Biogen, Roche, Merck, NHMRC, Pennycook Foundation, MSRA. HB has received compensation for same activities from Oxford Health Policy Forum, Merck, Biogen, Novartis. GI had travel/accommodations/meeting expenses funded by Bayer Schering, Biogen, Merck, Novartis, Sanofi Aventis, and Teva. AS has nothing to declare., (© Author(s) (or their employer(s)) 2023. No commercial re-use. See rights and permissions. Published by BMJ.)

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: Spinal cord lesions in multiple sclerosis (MS) are an important contributor to disability. Knowledge on the effect of disease-modifying treatment (DMT) on spinal lesion formation in MS is sparse, as cord outcome measures are seldom included in MS treatment trials. We aim to investigate whether intermediate- or high-efficacy DMTs (i/hDMT) can reduce spinal lesion formation, compared with low-efficacy DMTs (lDMT) and/or no treatment., Methods: Relapse-onset MS patients with ≥2 spinal MRIs (interval >3 months and <10 years) were retrospectively identified. The i/hDMT-group was defined as patients who were treated with i/hDMTs during ≥90% of spinal MRI follow-up time. Controls received lDMTs and/or no treatment ≥90% of follow-up duration. In a secondary analysis, only patients using lDMT for ≥90% of follow-up were considered controls. Patients were matched using propensity-scores. Cox proportional hazards models were used to estimate the risk of new spinal lesions., Results: 323 patients had ≥2 spinal cord MRIs. 49 satisfied i/hDMT and 168 control group criteria. 34 i/hDMT patients were matched to 83 controls. Patients in the i/hDMT-group were significantly less likely to develop new cord lesions at follow-up (HR 0.29 [0.12-0.75], p = 0.01). When the i/hDMT-group was matched to only controls using lDMT ≥90% of follow-up time (n = 17 and n = 25, respectively), there was no statistically significant difference (HR 1.01 [0.19-5.24], p = 0.99)., Conclusion: Treatment with intermediate- or high-efficacy DMTs reduces the risk of new spinal cord lesions compared with matched patients receiving no treatment and/or lDMTs. No conclusions could be drawn on whether i/hDMTs provide a larger risk reduction compared to only lDMTs (control group receiving lDMTs ≥90% of follow-up time)., Competing Interests: Declaration of Competing Interest Daniel Kreiter, Audrey Merry, Romy Spee and Oliver Gerlach have nothing to disclose; Raymond Hupperts received institutional research grants and fees for lectures and advisory boards from Biogen, Merck and Genzyme-Sanofi., (Copyright © 2023 The Author(s). Published by Elsevier B.V. All rights reserved.)

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.)

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.

Importance: Natalizumab cessation is associated with a risk of rebound disease activity. It is important to identify the optimal switch disease-modifying therapy strategy after natalizumab to limit the risk of severe relapses., Objectives: To compare the effectiveness and persistence of dimethyl fumarate, fingolimod, and ocrelizumab among patients with relapsing-remitting multiple sclerosis (RRMS) who discontinued natalizumab., Design, Setting, and Participants: In this observational cohort study, patient data were collected from the MSBase registry between June 15, 2010, and July 6, 2021. The median follow-up was 2.7 years. This was a multicenter study that included patients with RRMS who had used natalizumab for 6 months or longer and then were switched to dimethyl fumarate, fingolimod, or ocrelizumab within 3 months after natalizumab discontinuation. Patients without baseline data were excluded from the analysis. Data were analyzed from May 24, 2022, to January 9, 2023., Exposures: Dimethyl fumarate, fingolimod, and ocrelizumab., Main Outcomes and Measures: Primary outcomes were annualized relapse rate (ARR) and time to first relapse. Secondary outcomes were confirmed disability accumulation, disability improvement, and subsequent treatment discontinuation, with the comparisons for the first 2 limited to fingolimod and ocrelizumab due to the small number of patients taking dimethyl fumarate. The associations were analyzed after balancing covariates using an inverse probability of treatment weighting method., Results: Among 66 840 patients with RRMS, 1744 had used natalizumab for 6 months or longer and were switched to dimethyl fumarate, fingolimod, or ocrelizumab within 3 months of natalizumab discontinuation. After excluding 358 patients without baseline data, a total of 1386 patients (mean [SD] age, 41.3 [10.6] years; 990 female [71%]) switched to dimethyl fumarate (138 [9.9%]), fingolimod (823 [59.4%]), or ocrelizumab (425 [30.7%]) after natalizumab. The ARR for each medication was as follows: ocrelizumab, 0.06 (95% CI, 0.04-0.08); fingolimod, 0.26 (95% CI, 0.12-0.48); and dimethyl fumarate, 0.27 (95% CI, 0.12-0.56). The ARR ratio of fingolimod to ocrelizumab was 4.33 (95% CI, 3.12-6.01) and of dimethyl fumarate to ocrelizumab was 4.50 (95% CI, 2.89-7.03). Compared with ocrelizumab, the hazard ratio (HR) of time to first relapse was 4.02 (95% CI, 2.83-5.70) for fingolimod and 3.70 (95% CI, 2.35-5.84) for dimethyl fumarate. The HR of treatment discontinuation was 2.57 (95% CI, 1.74-3.80) for fingolimod and 4.26 (95% CI, 2.65-6.84) for dimethyl fumarate. Fingolimod use was associated with a 49% higher risk for disability accumulation compared with ocrelizumab. There was no significant difference in disability improvement rates between fingolimod and ocrelizumab., Conclusion and Relevance: Study results show that among patients with RRMS who switched from natalizumab to dimethyl fumarate, fingolimod, or ocrelizumab, ocrelizumab use was associated with the lowest ARR and discontinuation rates, and the longest time to first relapse.

Importance: Autologous hematopoietic stem cell transplant (AHSCT) is available for treatment of highly active multiple sclerosis (MS)., Objective: To compare the effectiveness of AHSCT vs fingolimod, natalizumab, and ocrelizumab in relapsing-remitting MS by emulating pairwise trials., Design, Setting, and Participants: This comparative treatment effectiveness study included 6 specialist MS centers with AHSCT programs and international MSBase registry between 2006 and 2021. The study included patients with relapsing-remitting MS treated with AHSCT, fingolimod, natalizumab, or ocrelizumab with 2 or more years study follow-up including 2 or more disability assessments. Patients were matched on a propensity score derived from clinical and demographic characteristics., Exposure: AHSCT vs fingolimod, natalizumab, or ocrelizumab., Main Outcomes: Pairwise-censored groups were compared on annualized relapse rates (ARR) and freedom from relapses and 6-month confirmed Expanded Disability Status Scale (EDSS) score worsening and improvement., Results: Of 4915 individuals, 167 were treated with AHSCT; 2558, fingolimod; 1490, natalizumab; and 700, ocrelizumab. The prematch AHSCT cohort was younger and with greater disability than the fingolimod, natalizumab, and ocrelizumab cohorts; the matched groups were closely aligned. The proportion of women ranged from 65% to 70%, and the mean (SD) age ranged from 35.3 (9.4) to 37.1 (10.6) years. The mean (SD) disease duration ranged from 7.9 (5.6) to 8.7 (5.4) years, EDSS score ranged from 3.5 (1.6) to 3.9 (1.9), and frequency of relapses ranged from 0.77 (0.94) to 0.86 (0.89) in the preceding year. Compared with the fingolimod group (769 [30.0%]), AHSCT (144 [86.2%]) was associated with fewer relapses (ARR: mean [SD], 0.09 [0.30] vs 0.20 [0.44]), similar risk of disability worsening (hazard ratio [HR], 1.70; 95% CI, 0.91-3.17), and higher chance of disability improvement (HR, 2.70; 95% CI, 1.71-4.26) over 5 years. Compared with natalizumab (730 [49.0%]), AHSCT (146 [87.4%]) was associated with marginally lower ARR (mean [SD], 0.08 [0.31] vs 0.10 [0.34]), similar risk of disability worsening (HR, 1.06; 95% CI, 0.54-2.09), and higher chance of disability improvement (HR, 2.68; 95% CI, 1.72-4.18) over 5 years. AHSCT (110 [65.9%]) and ocrelizumab (343 [49.0%]) were associated with similar ARR (mean [SD], 0.09 [0.34] vs 0.06 [0.32]), disability worsening (HR, 1.77; 95% CI, 0.61-5.08), and disability improvement (HR, 1.37; 95% CI, 0.66-2.82) over 3 years. AHSCT-related mortality occurred in 1 of 159 patients (0.6%)., Conclusion: In this study, the association of AHSCT with preventing relapses and facilitating recovery from disability was considerably superior to fingolimod and marginally superior to natalizumab. This study did not find evidence for difference in the effectiveness of AHSCT and ocrelizumab over a shorter available follow-up time.

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: Over the decades, several natural history studies on patients with primary (PPMS) or secondary progressive multiple sclerosis (SPMS) were reported from international registries. In PPMS, a consistent heterogeneity on long-term disability trajectories was demonstrated. The aim of this study was to identify subgroups of patients with SPMS with similar longitudinal trajectories of disability over time., Methods: All patients with MS collected within Big MS registries who received an SPMS diagnosis from physicians (cohort 1) or satisfied the Lorscheider criteria (cohort 2) were considered. Longitudinal Expanded Disability Status Scale (EDSS) scores were modelled by a latent class growth analysis (LCGA), using a non-linear function of time from the first EDSS visit in the range 3-4., Results: A total of 3613 patients with SPMS were included in the cohort 1. LCGA detected three different subgroups of patients with a mild (n=1297; 35.9%), a moderate (n=1936; 53.6%) and a severe (n=380; 10.5%) disability trajectory. Median time to EDSS 6 was 12.1, 5.0 and 1.7 years, for the three groups, respectively; the probability to reach EDSS 6 at 8 years was 14.4%, 78.4% and 98.3%, respectively. Similar results were found among 7613 patients satisfying the Lorscheider criteria., Conclusions: Contrary to previous interpretations, patients with SPMS progress at greatly different rates. Our identification of distinct trajectories can guide better patient selection in future phase 3 SPMS clinical trials. Additionally, distinct trajectories could reflect heterogeneous pathological mechanisms of progression., Competing Interests: Competing interests: AS received research support from MSBase. JL received research support from Innosuisse—Swiss Innovation Agency, Biogen and Novartis; he served on advisory boards for Biogen, Novartis, Roche and Teva. SV received consulting and lecture 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. 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 PI for projects or received unrestricted research support from Biogen Idec, Merck Serono, TEVA, Sanofi-Genzyme and Bayer-Schering; his MS research is funded by the Swedish Research Council and the Swedish Brain Foundation. RH is an employee of Biogen and holds a stock. FP is an employee of Biogen. MM has served on scientific advisory board for Biogen Idec and Teva; and has received honoraria for lecturing from Biogen Idec, Merck Serono, Sanofi-Aventis and Teva. NK-H has received honoraria for lecturing and participating in advisory councils, travel expenses for attending congresses and meetings, and financial support for monitoring the Danish Multiple Sclerosis Treatment Register from Bayer-Schering, Merck Serono, Biogen Idec, Teva, Sanofi-Aventis and Novartis. PSS has served on scientific advisory boards for Merck Serono, Teva, Novartis, Sanofi-Aventis and Biogen Idec; has received research support from Biogen Idec, Novartis and Sanofi-Aventis; and received speaker honoraria from Merck Serono, Novartis, Teva, Sanofi-Aventis, Biogen Idec and Genzyme. TS received compensation for serving on scientific advisory boards, honoraria for consultancy and funding for travel from Biogen; and speaker honoraria from Novartis. AvdW reported receiving grants from National Health and Medical Research Council (NHMRC), Novartis, Roche and MS Research Australia; and personal fees from Biogen, Merck, Novartis and Roche. DH received compensation for travel, speaker honoraria and consultant fees from Biogen, Novartis, Merck Healthcare (Darmstadt, Germany), Bayer, Sanofi, Roche and Teva, as well as support for research activities from Biogen. She was also supported by the Charles University: Cooperation Program in neuroscience. EH received honoraria/research support from Biogen, Merck Serono, Novars, Roche and Teva; has been a member of advisory boards for Actelion, Biogen, Celgene, Merck Serono, Novars and Sanofi Genzyme. 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 Canadian Institutes of Health Research. SE received speaker honoraria and consultant fees from Biogen Idec, Novartis, Merck, Bayer, Sanofi Genzyme, Roche and Teva. FG received honoraria or research funding from Biogen, Genzyme, Novartis, Teva Neurosciences, Mitsubishi and ONO Pharmaceuticals. OG has nothing to disclose. MT received travel grants from Novartis, Bayer-Schering, Merck and Teva; and has participated in clinical trials by Sanofi Aventis, Roche and Novartis. SO has nothing to disclose. OS has received honoraria and consulting fees from Bayer Schering, Novartis, Merck, Biogen and Genzyme companies. VVP received travel grants from Merck Healthcare (Darmstadt, Germany), Biogen, Sanofi, Bristol Meyer Squibb, Almirall and Roche. His institution has received research grants and consultancy fees from Roche, Biogen, Sanofi, Merck Healthcare (Darmstadt, Germany), Bristol Meyer Squibb, Janssen, Almirall and Novartis Pharma. MJS 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. JP accepted travel compensation from Novartis, Biogen, Genzyme and Teva; and speaking honoraria from Biogen, Novartis, Genzyme and Teva. RA received honoraria as a speaker and for serving on scientific advisory boards from Bayer, Biogen, GSK, Merck, Novartis, Roche and Sanofi-Genzyme. PAM received speakers fees and travel grants from Novartis, Biogen, T’évalua and Sanofi. RG has nothing to disclose. SM has received a MENACTRIMS clinical fellowship grant (2020). TC-T received speaking/consulting fees and/or travel funding from Bayer, Biogen, Merck, Novartis, Roche, Sanofi-Genzyme and Teva. CZ has nothing to disclose. KdG has nothing to disclose. JLS-M 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. BY and SK have nothing to disclose. MPS has received consulting fees from Biogen, Merck, Teva, Genzyme, Roche, Novartis, GeNeuro and MedDay. TK reported receiving grants from MS Research Australia and grants, personal fees and non-financial support from Biogen; personal fees and non-financial support from Sanofi Genzyme and Merck; personal fees from Roche, Novartis, WebMD Global, Teva and BioCSL; and grants from NHMRC, MS Research Australia, ARSEP-OFSEP, UK MS Society and Medical Research Future Fund. HB’s institution (Monash University) received compensation for consulting, talks, and advisory/steering board activities from Alfred Health, Biogen, Merck, Novartis, Roche and UCB pharma; research support from Biogen, Merck, Roche, MS Australia, National Health and Medical Research (Australia) and the Medical Research Future Fund (Australia), the Pennycook Foundation, Novartis and Roche. He has received personal compensation for steering group activities from Oxford Health Policy Forum., (© Author(s) (or their employer(s)) 2023. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Unemployment is common among people with multiple sclerosis (pwMS) and has been associated with subjective cognitive difficulties, specifically in memory, attention, and executive functioning. However, longitudinal research on subjective cognitive difficulties and employment is scarce., Objective: We investigated whether subjective cognitive impairment (SCI), based on the clinical cut-off score of the MS Neuropsychological Screening Questionnaire (MSNQ), was associated with work status and negative work events (NWE) at baseline and after 2 years. Moreover, we investigated whether four MSNQ subdomains were related to work status and NWE., Methods: 287 participants (77.4% female, median age = 42 years) completed questionnaires on subjective cognitive functioning, depression, anxiety, and fatigue, and completed the Symbol Digit Modalities Test (SDMT). After baseline comparisons, logistic regression analyses were performed, with work status and NWE at baseline, and employment change and NWE change within 2 years after baseline as dependent variables. Independent variables included SCI and the MSNQ domains. Covariates anxiety, depression, fatigue, and SDMT were added., Results: SCI, depression and anxiety were associated with work status ( Nagelkerke R 2 = .286), but only SCI was associated with employment change ( Nagelkerke R 2 = .164). No predictors were associated with NWE at baseline or follow-up. In addition, no MSNQ subdomain was related to work status, employment change or NWE., Conclusion: Unemployed pwMS and pwMS with a deteriorated work status reported more cognitive difficulties after 2 years than employed pwMS or pwMS with a stable work status. In addition, depression, and anxiety were associated with work status., Competing Interests: The authors declare no conflict of interest., (© 2022 The Authors.)

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: Symptoms of anxiety and depression affect the daily life of people with multiple sclerosis (MS). This study examined work difficulties and their relationship with anxiety, depression and coping style in people with MS., Methods: 219 employed people with MS (median age  =  43 years, 79% female) completed questionnaires on anxiety, depression, coping style, demographics and work difficulties, and underwent a neurological examination. Two regression analyses were performed with work difficulties as the dependent variable and either anxiety or depression as continuous independent variables. Coping style, age, gender, educational level, MS-related disability and disease duration were added as additional predictors, as well as interaction terms between coping style and either symptoms of depression or anxiety., Results: A significant model was found ( F (10,205)   =  13.14, p  < 0.001, R 2   =  0.39) in which anxiety, emotion- and avoidance-oriented coping and MS-related disability were positively related to work difficulties. The analysis of depression resulted in a significant model ( F (10,205)   =  14.98, p  < 0.001, R 2   =  0.42) in which depression, emotion- and avoidance-oriented coping and MS-related disability were positively related to work difficulties. None of the interaction effects were significant., Conclusions: Work difficulties were positively related to anxiety, depression, emotion- and avoidance-oriented coping and MS-related disability in workers with MS., Competing Interests: Declaration of conflicting interests: The author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: Disclosure: E. van Egmond, K. van der Hiele, D. van Gorp, J. van der Klink, M. Reneman, E. Beenakker, K. de Gans, B.M. van Geel, O. Gerlach, J. Mostert, and H. Middelkoop report no conflict of interest. P. Jongen received honoraria from Bayer Netherlands and Orikami Personalized Health Care, Netherlands, for consultancy activities and is chairman of the MSmonitor foundation, Netherlands. J. van Eijk received honoraria for lectures and honoraria for advisory boards from Sanofi Genzyme, Roche, Merck Serono, Novartis and Teva. S. Frequin received honoraria for lectures, grants for research and honoraria for advisory boards from Sanofi Genzyme, Merck Serono, Novartis, Biogen and Roche. G. Hengstman has received consultation fees and grants from Biogen, BMS, Genzyme-Sanofi, Merck BV, Novartis Pharma and Roche. W. Verhagen received honoraria for lectures from Biogen and Merck Serono, reimbursement for hospitality from Biogen, Sanofi Genzyme and Merck Serono, and honoraria for advisory boards from Merck Serono. L.H. Visser received honoraria for lectures and honoraria for advisory boards from Merck Serono and Novartis., (© The Author(s), 2022.)

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.)

Background: A delayed onset of treatment effect, termed therapeutic lag, may influence the assessment of treatment response in some patient subgroups., Objectives: The objective of this study is to explore the associations of patient and disease characteristics with therapeutic lag on relapses and disability accumulation., Methods: Data from MSBase, a multinational multiple sclerosis (MS) registry, and OFSEP, the French MS registry, were used. Patients diagnosed with MS, minimum 1 year of exposure to MS treatment and 3 years of pre-treatment follow-up, were included in the analysis. Studied outcomes were incidence of relapses and disability accumulation. Therapeutic lag was calculated using an objective, validated method in subgroups stratified by patient and disease characteristics. Therapeutic lag under specific circumstances was then estimated in subgroups defined by combinations of clinical and demographic determinants., Results: High baseline disability scores, annualised relapse rate (ARR) ⩾ 1 and male sex were associated with longer therapeutic lag on disability progression in sufficiently populated groups: females with expanded disability status scale (EDSS) < 6 and ARR < 1 had mean lag of 26.6 weeks (95% CI = 18.2-34.9), males with EDSS < 6 and ARR < 1 31.0 weeks (95% CI = 25.3-36.8), females with EDSS < 6 and ARR ⩾ 1 44.8 weeks (95% CI = 24.5-65.1), and females with EDSS ⩾ 6 and ARR < 1 54.3 weeks (95% CI = 47.2-61.5)., Conclusions: Pre-treatment EDSS and ARR are the most important determinants of therapeutic lag.

B-cells contribute to MS pathogenesis. The association of circulating B-cell phenotypes with combined unique active lesions (CUA) on MRI at 48 weeks follow-up was investigated in 50 interferon beta-treated MS patients. Transitional B-cell proportions were lower in participants with CUA at week 0 and 48 [p = 0.004, p = 0.002]. A decrease in circulating anti-EBNA-1 IgG levels between week 0 and 48 associated with absence of CUA [p = 0.047], but not with B-cell profiles. In a multi-factor model for CUA-risk, transitional B-cell proportions contributed independent from NK/T-cell ratio, change in anti-EBNA-1 IgG, and vitamin D supplementation. Transitional B-cells may predict treatment response in MS., (Copyright © 2021 The Authors. Published by Elsevier B.V. All rights reserved.)

Background and Objectives: Research in Multiple Sclerosis (MS) has recently focused on extracting knowledge from real-world clinical data sources. This type of data is more abundant than data produced during clinical trials and potentially more informative about real-world clinical practice. However, this comes at the cost of less curated and controlled data sets. In this work we aim to predict disability progression by optimally extracting information from longitudinal patient data in the real-world setting, with a special focus on the sporadic sampling problem., Methods: We use machine learning methods suited for patient trajectories modeling, such as recurrent neural networks and tensor factorization. A subset of 6682 patients from the MSBase registry is used., Results: We can predict disability progression of patients in a two-year horizon with an ROC-AUC of 0.85, which represents a 32% decrease in the ranking pair error (1-AUC) compared to reference methods using static clinical features., Conclusions: Compared to the models available in the literature, this work uses the most complete patient history for MS disease progression prediction and represents a step forward towards AI-assisted precision medicine in MS., Competing Interests: Declaration of Competing Interest The authors declare the following conflicts of interest., (Copyright © 2021. Published by Elsevier B.V.)

Background: Prolonged-release fampridine (PR-FAM) 10-mg tablet twice daily is the only approved pharmacological treatment for improvement of walking ability in adults with multiple sclerosis (MS). LIBERATE assessed the safety/effectiveness of PR-FAM in the real-world., Objectives: The aim of this study was to collect additional safety data, including the incidence rate of seizures and other adverse events (AEs) of interest, from patients with MS taking PR-FAM in routine clinical practice (including patients aged ≥ 65 years and those with pre-existing cardiovascular risk factors). Other objectives included change over time in patient-reported evaluation of physical and psychological impact of MS while taking PR-FAM, and change over time in physician-reported assessment of walking ability in MS patients taking PR-FAM., Methods: Patients with MS newly prescribed PR-FAM were recruited (201 sites, 13 countries). Demographic/safety data were collected at enrolment through 12 months. Physician-rated Clinical Global Impression of Improvement (CGI-I) scores for walking ability, and Multiple Sclerosis Impact Scale-29 (MSIS-29) were assessed., Results: Safety analysis included 4646 patients with 3534.8 patient-years of exposure; median (range) age, 52.6 (21-85) years, 87.3% < 65 years, and 65.7% women. Treatment-emergent AEs (TEAEs) were reported in 2448 (52.7%) patients, and serious TEAEs were reported in 279 (6.0%) patients, of whom 37 (< 1%) experienced treatment-emergent serious AEs (TESAEs) considered related to PR-FAM. AEs of special interest (AESI) occurred in 1799 (38.7%) patients, and serious AESI in 128 (2.8%) patients. Seventeen (< 1%) patients experienced actual events of seizure. Overall, 1158 (24.9%) patients discontinued treatment due to lack of efficacy. At 12 months, a greater proportion of patients on-treatment had improvement from baseline in CGI-I for walking ability versus those who discontinued (61% vs. 11%; p <  0.001). MSIS-29 physical impact score improved significantly for patients on-treatment for 12 months versus those who discontinued (mean change, baseline to 12 months: - 9.99 vs. - 0.34 points; p <  0.001). Results were similar for MSIS-29 psychological impact., Conclusion: No new safety concerns were identified in this real-world study, suggesting that routine risk-minimization measures are effective. CGI-I and MSIS-29 scores after 12 months treatment with PR-FAM treatment show clinical benefits consistent with those previously reported., Trial Registration: ClinicalTrials.gov: NCT01480063., (© 2021. The Author(s).)

Objective: To compare the clinical effectiveness of high- and low-efficacy treatments in patients with recently active and inactive secondary progressive multiple sclerosis (SPMS) after accounting for therapeutic lag., Methods: Patients treated with high-efficacy (natalizumab, alemtuzumab, mitoxantrone, ocrelizumab, rituximab, cladribine, fingolimod) or low-efficacy (interferon beta, glatiramer acetate, teriflunomide) therapies after SPMS onset were selected from MSBase and Observatoire Français de la Sclérose en Plaques (OFSEP), 2 large observational cohorts. Therapeutic lag was estimated for each patient from their demographic and clinical characteristics. Propensity score was used to match patients treated with high- and low-efficacy therapies. Outcomes after the period of therapeutic lag was disregarded were compared in paired, pairwise-censored analyses., Results: One thousand patients were included in the primary analysis. Patients with active SPMS treated with high-efficacy therapy experienced less frequent relapses than those on low-efficacy therapy (hazard ratio [HR] 0.7, p = 0.006). In patients with inactive SPMS, there was no evidence for a difference in relapse frequency between groups (HR 0.8, p = 0.39). No evidence for a difference in the risk of disability progression was observed., Conclusion: In treated patients with SPMS, high-efficacy therapy is superior to low-efficacy therapy in reducing relapses in patients with active but not those with inactive SPMS. However, more potent therapies do not offer an advantage in reducing disability progression in this patient group., Classification of Evidence: This study provides Class III evidence that high-efficacy therapy is superior to low-efficacy therapy in reducing relapses in patients with active SPMS, although we did not find a difference in disability progression between patients treated with high- and low-efficacy therapy., (© 2021 American Academy of Neurology.)

Background: Multiple sclerosis (MS) poses a major threat to sustainable employability. Identifying conditions and factors that promote work participation is of great importance. Our objective was to explore the contribution of personality traits in explaining occupational functioning in MS., Methods: 241 participants with relapsing-remitting MS (78% female, median age: 42.0 years, median EDSS: 2.0) and 60 healthy controls (70% female, median age: 45.0 years) underwent neuropsychological and neurological examinations and completed questionnaires. Multivariate logistic and linear regression analyses were conducted to examine relations between personality traits and self-reported occupational functioning, while accounting for known correlates., Results: Personality traits were not associated with self-reported occupational functioning when correcting for known correlates. A higher impact of fatigue (B = -0.05, p = .005 and B = -0.04, p = .009) and depression (B = -0.22, p = .008 and B = -0.21, p = .01) were associated with no paid job (R 2  = 0.13) and considering to reduce work hours (R 2  = 0.12). A higher impact of fatigue (B = -0.05, p = .008, β = 0.46, p = .001 and β = -0.36, p = .001) was associated with absenteeism from work (R 2  = 0.15), more presenteeism (R 2  = 0.35) and lower work ability (R 2  = 0.25). A higher impact of fatigue (β = 0.46, p = .001) and anxiety (β = 0.25, p = .001) were associated with more work difficulties (R 2  = 0.54)., Conclusion: Personality traits did not explain additional variance in self-reported occupational functioning in persons with relapsing-remitting MS with mild disability. The impact of fatigue was the main and most consistent correlate of occupational functioning, often combined with depression or anxiety. Total explained variance of the models was limited, emphasizing the need to additionally examine other (contextual) factors when considering occupational challenges in MS., (Copyright © 2021 The Authors. Published by Elsevier B.V. All rights reserved.)

Introduction: Vitamin D has long been known for its immune-modulating effects, next to its function in calcium metabolism. As a consequence, poor vitamin D status has been associated with many diseases including multiple sclerosis (MS). Epidemiological studies suggest an association between a poor vitamin D status and development of MS and a poor vitamin D status is associated with more relapses and faster progression after patients are diagnosed with MS., Area’s Covered: The aim of the authors was to review the role of vitamin D supplementation in the treatment of MS. Pubmed was used to review literature with a focus of vitamin D supplementation trials and meta-analyses in MS., Expert Opinion: There is no solid evidence to support the application of vitamin D therapy, based on current available supplementation trials, although there are some promising results in the clinically isolated syndrome (CIS) patients and young MS patients early after initial diagnosis. The authors recommend further larger clinical trials with selected patient groups, preferable CIS patients and young patients at the time of diagnosis, using vitamin D 3 supplements to reach a 100 nmol/l level, to further investigate the effects of vitamin D supplementation in MS.

NK/T-cell ratios predict disease activity in relapsing remitting multiple sclerosis (RRMS). We investigated in 50 RRMS patients whether interleukin-2 receptor alpha-chain (IL-2Rα) expression and shedding associates with NK/T-cell balance, as suggested by daclizumab-trials in RRMS. A subsample (N = 31) was genotyped for IL2RA-associated MS risk SNPs. CD56 bright NK-cell/IL-17A + CD4 + T-cell ratios correlated negatively with plasma and PBMC-culture supernatant sIL-2Rα-levels [R = -0.209; p = 0.038 and R = -0.254; p = 0.012, resp.], and with CD4 + T-cell CD25 MFI [R = -0.341; p = 0.001]. Carriers of the rs3118470 risk-allele showed higher sIL-2Rα-levels (P = 0.031) and a lower CD56 bright NK-cell/IL-17A + CD4 + T-cell ratio (P = 0.038). Therefore, IL-2Rα may be involved in the interplay between NK-cells and T-cells., (Copyright © 2021 The Author(s). Published by Elsevier B.V. All rights reserved.)