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

Background: Ongoing controversy exists regarding optimal management of disease modifying therapy (DMT) in older people with multiple sclerosis (pwMS). There is concern that the lower relapse rate, combined with a higher risk of DMT-related infections and side effects, may alter the risk-benefit balance in older pwMS. Given the lack of pwMS above age 60 in randomised controlled trials, the comparative efficacy of high-efficacy DMTs such as ocrelizumab has not been shown in older pwMS. We aimed to evaluate the comparative effectiveness of ocrelizumab, a high-efficacy DMT, versus interferon/glatiramer acetate (IFN/GA) in pwMS over the age of 60., Methods: Using data from MSBase registry, this multicentre cohort study included pwMS above 60 who switched to or started on ocrelizumab or IFN/GA. We analysed relapse and disability outcomes after balancing covariates using an inverse probability treatment weighting (IPTW) method. Propensity scores were obtained based on age, country, disease duration, sex, baseline Expanded Disability Status Scale, prior relapses (all-time, 12 months and 24 months) and prior DMT exposure (overall number and high-efficacy DMTs). After weighting, all covariates were balanced. Primary outcomes were time to first relapse and annualised relapse rate (ARR). Secondary outcomes were 6-month confirmed disability progression (CDP) and confirmed disability improvement (CDI)., Results: A total of 248 participants received ocrelizumab, while 427 received IFN/GA. The IPTW-weighted ARR for ocrelizumab was 0.01 and 0.08 for IFN/GA. The IPTW-weighted ARR ratio was 0.15 (95% CI 0.06 to 0.33, p<0.001) for ocrelizumab compared with IFN/GA. On IPTW-weighted Cox regression models, HR for time to first relapse was 0.13 (95% CI 0.05 to 0.26, p<0.001). The hazard of first relapse was significantly reduced in ocrelizumab users after 5 months compared with IFN/GA users. However, the two groups did not differ in CDP or CDI over 3.57 years., Conclusion: In older pwMS, ocrelizumab effectively reduced relapses compared with IFN/GA. Overall relapse activity was low. This study adds valuable real-world data for informed DMT decision making with older pwMS. Our study also confirms that there is a treatment benefit in older people with MS, given the existence of a clear differential treatment effect between ocrelizumab and IFN/GA in the over 60 age group., Competing Interests: Competing interests: YCF received travel compensation from Biogen, National Health and Medical Research Council, Multiple Sclerosis Research Australia and Australian and New Zealand Association of Neurologists. MG is currently working on observational studies funded by Biogen and Roche. DM has received honoraria from Novartis. CZ has nothing to disclose. KB has received honoraria for presentations and/or educational support from Biogen, Sanofi Genzyme, Merck, Roche, Alexion and Teva and serves on medical advisory boards for Merck and Biogen. MZ has received conference travel support from Novartis and Roche, and research support from the Australian Government Research Training Program and MS Research Australia. WZY: received honoraria from Merck and Novartis. VJ receives research grant support form F.Hoffmann La-Roche, MS Research Australia and the National Health and Medical Research Council of Australia (NHMRC 1156519). MM has received research support from National Health and Medical Research Council, Medical Research Future Fund, Brain Foundation, Charles and Sylvia Viertel Foundation, MS Research Australia, Merck and Ku Leuven University, served on advisory board for Merck, has received speaker honoraria from Merck and Biogen. OS received honoraria and consulting fees from Bayer Schering, Novartis, Merck, Biogen and Genzyme. SO has nothing to disclose. FP received personal compensation for serving on advisory board by Almirall, Alexion, Biogen, Bristol, Merck, Novartis and Roche and received research grant by Biogen, Merck and Roche and by FISM, Reload Association (Onlus), Italian Health Minister, University of Catania. 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. MPA received honoraria as consultant on scientific advisory boards by Biogen, Bayer-Schering, Merck, Teva and Sanofi-Aventis and has received research grants by Biogen, Bayer-Schering, Merck, Teva and Novartis. TK served on scientific advisory boards for MS International Federation and WHO, 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, Roche, Sanofi-Genzyme, Teva, BioCSL and Merck and received research or educational event support from Biogen, Novartis, Genzyme, Roche, Celgene and Merck. DH supported by the Charles University: Cooperatio Programme in Neuroscience, by the project National Institute for Neurological Research (Programme EXCELES, ID Project No. LX22NPO5107)—funded by the European Union – Next Generation EU, General University Hospital in Prague project MH CZ-DRO-VFN64165 and 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 Inc. EKH received honoraria/research support from Biogen, Merck Serono, Novars, Roche, and Teva; has been member of advisory boards for Actelion, Biogen, Celgene, Merck Serono, Novars, and Sanofi Genzyme; received honoraria/research support from Biogen, Merck Serono, Novars, Roche, and Teva; has been member of advisory boards for Actelion, Biogen, Celgene, Merck Serono, Novars and Sanofi Genzyme; and has been supported by the Czech Ministry of Education—project Cooperatio LF1, research area Neuroscience, and the project National Institute for Neurological Research (Programme EXCELES, ID project No LX22NPO5107)—funded by the European Union-Next Generation EU. BW-G participated in speaker’s bureaus and/or served as a consultant and received grants from Biogen, EMD Serono, Novartis, Genentech, Celgene/Bristol Meyers Squibb, Sanofi Genzyme, Bayer, Janssen and Horizon; she also serves in the editorial board for BMJ Neurology, Children, CNS Drugs, MS International and Frontiers Epidemiology. JLS received travel compensation from Novartis, Biogen, Roche and Merck and her institution receives the honoraria for talks and advisory board commitment as well as research grants from Biogen, Merck, Roche, TEVA and Novartis. CB received conference travel support from Biogen, Novartis, Bayer-Schering, Merck and Teva; has participated in clinical trials by Sanofi Aventis, Roche and Novartis. 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. AvdW served on advisory boards for Novartis, Biogen, Merck and Roche and NervGen, received research grants from National Health and Medical Research Council of Australia, MS Research Australia, Novartis, Biogen, Merck and Roche, received speaker’s honoraria and travel support from Novartis, Roche, Biogen and Merck and is currently a coprincipal investigator on a cosponsored observational study with Roche. HB’s Institution has received compensation for advisory boards or lecture fees from Novartis, Biogen, Merck, UCB Pharma and Roche and receives research funding from Novartis, Biogen, Merck, Roche, The National Health and Medical Research Council of Australia, The Medical Research Future Fund (Australia), Monash Partners, the Trish MS Foundation, The Pennycook Foundation, and MS Australia; he also receives personal compensation as the Managing Director of the MSBase Foundation and from the Oxford Health Policy Forum Brain Health Initiative., (© Author(s) (or their employer(s)) 2024. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: In Australia, tixagevimab/cilgavimab 150 mg/150 mg was a government-funded pre-exposure prophylaxis for COVID-19 people with multiple sclerosis (pwMS) and other neuroimmunological conditions (pwNIc) treated with anti-CD20 antibodies or sphingosine-1-phosphate receptor modulators were eligible., Objective: To analyse the roll-out, uptake and real-world efficacy of tixagevimab/cilgavimab in the prevention and severity of COVID-19. To assess compliance with uptake depending on the location of delivery., Methods: We undertook a single-centre study. 440 pwMS and pwNIc were eligible. Logistic regression was used to assess predictors of COVID-19 during follow-up and to assess predictors of uptake among those who consented., Results: Of the eligible pwMS and pwNIc in our service, 52.7% (233/440) requested a consultation and were included in this study. Consultation resulted in 71.7% of people (167/233) receiving the treatment. Of these, 94.0% (157/167) had received three or more COVID-19 vaccines. Among those who received a single dose of tixagevimab/cilgavimab, 19.16% (32/167) tested positive for COVID-19 during the observational window. The majority of these were on ocrelizumab (68.8% (22/32)). None of those with COVID-19 required hospitalisation or supplemental oxygen. There was no difference in odds of COVID-19 during the observation period between those who received and did not receive tixagevimab/cilgavimab (adjusted OR, aOR 2.16 (95% CI 0.82 to 6.85), p=0.43). Uptake of tixagevimab/cilgavimab was highest when offered at the hospital infusion centre (aOR 3.09 (95% CI 1.08 to 9.94) relative to referral to the local pharmacy, p=0.04)., Conclusion: Tixagevimab/cilgavimab administration did not protect against subsequent COVID-19 in our cohort. Compliance with uptake was influenced by administration location., Competing Interests: Competing interests: AvdW 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. MM has served on advisory board for Merck, has received speaker honoraria from Merck and Biogen. Her institution receives funding from Merck, Australian National Health Medical Research Council, Brain Foundation, Charles and Sylvia Viertel Foundation, Bethlehem Griffith Foundation and MS Research Australia. WZY has received speaker honoraria from Merck & Novartis. LR served on advisory boards from Biogen, Merck and Roche She has received speaker’s honoraria and travel support from Biogen, Novartis, Roche and Merck. HB 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; received compensation for same activities from Oxford Health Policy Forum, Merck, Biogen, Novartis. OS received travel support, speaker honoraria for Biogen, Merck, Genzyme and Novartis and served on scientific advisory board of Merck and Biogen. RW has received travel support from Merck, Roche and Honoraria from Biogen. MZ has received conference support from Roche. CN has no conflicts of interest. AR has no conflicts of interest. FB has received travel support from Biogen. NS has received conference support from Roche. TT has no conflicts of interest. YF has received travel support from Biogen., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Aggressive disease control soon after multiple sclerosis (MS) diagnosis may prevent irreversible neurological damage, and therefore early initiation of a high-efficacy disease-modifying therapy (DMT) is of clinical relevance., Objectives: Evaluate long-term clinical outcomes in patients with MS who initiated treatment with either natalizumab or a BRACETD therapy (interferon beta, glatiramer acetate, teriflunomide, or dimethyl fumarate)., Design: This retrospective analysis utilized data from MSBase to create a matched population allowing comparison of first-line natalizumab to first-line BRACETD., Methods: This study included patients who initiated treatment either with natalizumab or a BRACETD DMT within 1 year of MS diagnosis and continued treatment for ⩾6 months, after which patients could switch DMTs or discontinue treatment. Patients had a minimum follow-up time of ⩾60 months from initiation. A subgroup analysis compared the natalizumab group to patients in the BRACETD group who escalated therapy after 6 months. Outcomes included unadjusted annualized relapse rates (ARRs), time-to-first relapse, time-to-first confirmed disability improvement (CDI), and time-to-first confirmed disability worsening (CDW)., Results: After 1:1 propensity score matching, 355 BRACETD patients were matched to 355 natalizumab patients. Patients initiating natalizumab were less likely to experience a relapse over the duration of follow-up, with ARRs [95% confidence interval (CI)] of 0.080 (0.070-0.092) for natalizumab patients and 0.191 (0.178-0.205) for BRACETD patients ( p  < 0.0001). A Cox regression model of time-to-first relapse showed a reduced risk of relapse for natalizumab patients [hazard ratio (95% CI) of 0.52 (0.42-0.65); p  < 0.001] and a more favorable time-to-first CDI. The risk of CDW was similar between groups. The subgroup analysis showed an increased relapse risk as well as a significantly higher risk of CDW for BRACETD patients., Conclusion: Early initiation of natalizumab produced long-term benefits in relapse outcomes in comparison with BRACETD, regardless of a subsequent escalation in therapy., (© The Author(s), 2024.)

Ocrelizumab is an anti-CD20 monoclonal antibody (mAb) that has been shown in phase 3 clinical trials to reduce relapses and disease progression in multiple sclerosis (MS) patients. Prior to the approval of ocrelizumab, rituximab, a chimeric anti-CD20 mAb was used to treat MS. Rituximab is still used to treat MS in many countries outside of Australia and remains mainstay of treatment of many non-MS neuroimmunological and systemic inflammatory diseases. Rituximab is currently used in neuromyelitis optica spectrum disorder (NMOSD) and autoimmune encephalitis, in addition to its widespread usage in hematological malignancies and systemic inflammatory diseases. Ocrelizumab is currently approved in Australia for treatment of relapsing-remitting MS (RRMS). Neutropaenia is a rare complication of both ocrelizumab and rituximab treatment. This case series reports 12 patients who have experienced neutropaenia following ocrelizumab or rituximab treatment and aims to characterize the clinical parameters of neutropaenia experienced by these patients, including the severity and duration of neutropaenia, length of hospital admission, the types of subsequent infections experienced and types of treatment necessary before patients reached count recovery. The unpredictability of neutropaenia and potential for serious infections highlight the need for continued hematological monitoring for patients on B-cell depleting therapies and calls for careful patient counselling to provide guidance on whether to continue such therapies in patients who have experienced related neutropaenia., Competing Interests: Declaration of Competing Interest NS has received conference fee sponsorship from Roche. HB's institution receives funding from Biogen, Roche, Merck and Novartis for speaker engagements, study steering and advisory committee service. He is on the editorial board of Multiple Sclerosis and Related Disorders and the Steering committee of the Brain Health Initiative (Oxford Health Policy Forum). MM has served on advisory board for Merck, has received speaker honoraria from Merck, Biogen and Novartis. Her institution receives funding from Merck, Australian National Health Medical Research Council, Brain Foundation, Charles and Sylvia Viertel Foundation, and MS Research Australia., (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.

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.)

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

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

Importance: Ocrelizumab, a humanized monoclonal antibody targeted against CD20+ B cells, reduces the frequency of relapses by 46% and disability worsening by 40% compared with interferon beta 1a in relapsing-remitting multiple sclerosis (MS). Rituximab, a chimeric monoclonal anti-CD20 agent, is often prescribed as an off-label alternative to ocrelizumab., Objective: To evaluate whether the effectiveness of rituximab is noninferior to ocrelizumab in relapsing-remitting MS., Design, Setting, and Participants: This was an observational cohort study conducted between January 2015 and March 2021. Patients were included in the treatment group for the duration of study therapy and were recruited from the MSBase registry and Danish MS Registry (DMSR). Included patients had a history of relapsing-remitting MS treated with ocrelizumab or rituximab, a minimum 6 months of follow-up, and sufficient data to calculate the propensity score. Patients with comparable baseline characteristics were 1:6 matched with propensity score on age, sex, MS duration, disability (Expanded Disability Status Scale), prior relapse rate, prior therapy, disease activity (relapses, disability accumulation, or both), magnetic resonance imaging lesion burden (missing values imputed), and country., Exposure: Treatment with ocrelizumab or rituximab after 2015., Main Outcomes and Measures: Noninferiority comparison of annualized rate of relapses (ARRs), with a prespecified noninferiority margin of 1.63 rate ratio. Secondary end points were relapse and 6-month confirmed disability accumulation in pairwise-censored groups., Results: Of the 6027 patients with MS who were treated with ocrelizumab or rituximab, a total of 1613 (mean [SD] age; 42.0 [10.8] years; 1089 female [68%]) fulfilled the inclusion criteria and were included in the analysis (898 MSBase, 715 DMSR). A total of 710 patients treated with ocrelizumab (414 MSBase, 296 DMSR) were matched with 186 patients treated with rituximab (110 MSBase, 76 DMSR). Over a pairwise censored mean (SD) follow-up of 1.4 (0.7) years, the ARR ratio was higher in patients treated with rituximab than in those treated with ocrelizumab (rate ratio, 1.8; 95% CI, 1.4-2.4; ARR, 0.20 vs 0.09; P < .001). The cumulative hazard of relapses was higher among patients treated with rituximab than those treated with ocrelizumab (hazard ratio, 2.1; 95% CI, 1.5-3.0). No difference in the risk of disability accumulation was observed between groups. Results were confirmed in sensitivity analyses., Conclusion: In this noninferiority comparative effectiveness observational cohort study, results did not show noninferiority of treatment with rituximab compared with ocrelizumab. As administered in everyday practice, rituximab was associated with a higher risk of relapses than ocrelizumab. The efficacy of rituximab and ocrelizumab administered at uniform doses and intervals is being further evaluated in randomized noninferiority clinical trials.

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.

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.

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: 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: Patients with relapsing-remitting multiple sclerosis commonly switch between disease-modifying therapies (DMTs). Identifying predictors of relapse when switching could improve outcomes., Objective: To determine predictors of relapse hazard when switching to cladribine., Methods: Data of patients who switched to cladribine, grouped by prior disease-modifying therapy (pDMT; interferon-β/glatiramer acetate, dimethyl fumarate, teriflunomide, fingolimod or natalizumab (NTZ)), were extracted from the MSBase Registry. Predictors of relapse hazard during the treatment gap and the first year of cladribine therapy were determined., Results: Of 513 patients, 22 relapsed during the treatment gap, and 38 within 1 year of starting cladribine. Relapse in the year before pDMT cessation predicted treatment gap relapse hazard (hazard ratio (HR) = 2.43, 95% confidence interval (CI)  = 1.03-5.71). After multivariable adjustment, relapse hazard on cladribine was predicted by relapse before pDMT cessation (HR = 2.00, 95% CI = 1.01-4.02), treatment gap relapse (HR = 6.18, 95% confidence interval (CI) = 2.65-14.41), switch from NTZ (HR compared to injectable therapies 4.08, 95% CI = 1.35-12.33) and age at cladribine start (HR = 0.96, 95% CI = 0.91-0.99)., Conclusion: Relapse during or prior to the treatment gap, and younger age, are of prognostic relevance in the year after switching to cladribine. Switching from NTZ is also independently associated with greater relapse hazard.

Background: To compare the effectiveness and treatment persistence of ocrelizumab, cladribine and natalizumab in patients with relapsing-remitting multiple sclerosis switching from fingolimod., Methods: Using data from MSBase registry, this multicentre cohort study included subjects who had used fingolimod for ≥6 months and then switched to ocrelizumab, cladribine or natalizumab within 3 months after fingolimod discontinuation. We analysed relapse and disability outcomes after balancing covariates using an inverse-probability-treatment-weighting method. Propensity scores for the three treatments were obtained using multinomial-logistic regression. Due to the smaller number of cladribine users, comparisons of disability outcomes were limited to natalizumab and ocrelizumab., Results: Overall, 1045 patients switched to ocrelizumab (n=445), cladribine (n=76) or natalizumab (n=524) after fingolimod. The annualised relapse rate (ARR) for ocrelizumab was 0.07, natalizumab 0.11 and cladribine 0.25. Compared with natalizumab, the ARR ratio (95% confidence interval [CI]) was 0.67 (0.47 to 0.96) for ocrelizumab and 2.31 (1.30 to 4.10) for cladribine; the hazard ratio (95% CI) for time to first relapse was 0.57 (0.40 to 0.83) for ocrelizumab and 1.18 (0.47 to 2.93) for cladribine. Ocrelizumab users had an 89% lower discontinuation rate (95% CI, 0.07 to 0.20) than natalizumab, but also a 51% lower probability of confirmed disability improvement (95% CI, 0.32 to 0.73). There was no difference in disability accumulation., Conclusion: After fingolimod cessation, ocrelizumab and natalizumab were more effective in reducing relapses than cladribine. Due to the low ARRs in all three treatment groups, additional observation time is required to determine if statistical difference in ARRs results in long-term disability differences., Competing Interests: Competing interests: CZ, OS, RM, AP, JK, MO, RK, SO, DM, IR and ZZ report no disclosures. VJ received conference travel support from Merck and Roche and speaker’s honoraria from Biogen and Roche outside of the submitted work. She receives research support from the Australian National Health and Medical Research Grant and MS Research Australia. MB received conference travel support from Biogen and Novartis. His institution has received research support from Biogen, Merck and Novartis. TK 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. JL-S received travel compensation from Novartis, Biogen, Roche and Merck. Her institution receives the honoraria for talks and advisory board commitment and research grants from Biogen, Merck, Roche, TEVA and Novartis. SJK received compensation for scientific advisory board activity from Merck and Roche. SH received honoraria and consulting fees from Novartis, Bayer Schering and Sanofi, and travel grants from Novartis, Biogen Idec and Bayer Schering. MS participated in, but not received honoraria for, advisory board activity for Biogen, Merck, Bayer Schering, Sanofi Aventis and Novartis. AvdW 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 also received grant support from the National Health and Medical Research Council of Australia and MS Research Australia. VVP has received travel grants from Merck Healthcare KGaA (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 KGaA (Darmstadt, Germany), Bristol Meyer Squibb, Janssen, Almirall and Novartis Pharma. JP received travel compensation from Novartis, Biogen, Genzyme and Teva, and speaking honoraria from Biogen, Novartis, Genzyme and Teva. DH received speaker honoraria and consulting fees from Biogen, Merck, Teva, Roche, Sanofi Genzyme and Novartis, as well as support for research activities from Biogen and Czech Ministry of Education. EKH received honoraria/research support from Biogen, Merck Serono, Novartis, Roche and Teva. GI received speaking honoraria from Biogen, Novartis, Sanofi, Merck, Roche, Almirall and Teva. 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. 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; he participated in Sanofi Aventis, Roche and Novartis clinical trials. MM has served on advisory board for Merck, has received speaker honoraria from Merck and Biogen. Her institution receives funding from Merck, Australian National Health Medical Research Council, Brain Foundation, Charles and Sylvia Viertel Foundation, Bethlehem Griffith Foundation and MS Research Australia. HB has received institutional (Monash University) funding from Biogen, F. Hoffmann-La Roche Ltd, Merck, Alexion, CSL and Novartis; has carried out contracted research for Novartis, Merck, F. Hoffmann-La Roche Ltd and Biogen; has taken part in speakers’ bureaus for Biogen, Genzyme, UCB, Novartis, F. Hoffmann-La Roche Ltd and Merck; has received personal compensation from Oxford Health Policy Forum for the Brain Health Steering Committee., (© Author(s) (or their employer(s)) 2022. No commercial re-use. See rights and permissions. Published by BMJ.)

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.)