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Background: Access to, standardization and reimbursement of multidisciplinary care for people with MS (PwMS) is lacking in many countries. Therefore, this study aims to describe the current multidisciplinary care for people with MS (PwMS) in Belgium and identify benefits, needs and future perspectives METHODS: A survey for PwMS questioned various aspects of MS and viewpoints on care. For MS nurses (MSN) and neurologists, employment, education, job-content, care organization and perspectives were inquired. Descriptive and univariate statistics were performed RESULTS: The PwMS survey comprised 916 respondents with a mean age of 46±12.7 years and 75,4 % of the respondents being female. The majority of the participants had relapsing remitting MS (60.8 %) and the mean patient determined disease steps (PDDS) was 2.0 (IQR=3). 65.3 % and 60.4 % of the PwMS reported having access to a multidisciplinary team (MDT) or MSN. Access to an MSN was associated with more frequent disease modifying treatment (p=.015), spasticity (p=.042) and gait treatment (p=.035), but also more physiotherapy (p=.004), driver's license adjustment (p<.001) and a higher employment rate (p=.004). MDT access was associated with more frequent symptomatic bladder treatment (p=.047), higher physiotherapy rate (p<.001), higher work- (p=.002), insurance- (p<.001) and home support measures (p=.019). PwMS without an available MDT more often indicated that MS care needs improvement (p<.001). MSN's (n = 22) were mainly funded through various budgets, including hospital and neurology practice budgets. Finally, 69 % and 75 % neurologists (n = 62) working without an MSN or MDT stated a need of such support and 61 % agreed that MDT's should be organized at hospital-network level CONCLUSION: MDT and MSN availability may enhance medical and socio-economic support for PwMS. Guidelines, alignment and reimbursement are needed., Competing Interests: Declaration of competing interest The authors declare that they have no conflict of interest to report., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background: Cerebrospinal fluid (CSF) kappa free light chain (κFLC) measures gained increasing interest as diagnostic markers in multiple sclerosis (MS). However, the lack of studies comparing assay-dependent diagnostic cutoff values hinders their use in clinical practice. Additionally, the optimal κFLC parameter for identifying MS remains a subject of ongoing debate., Objectives: The aim of this study was to compare same-sample diagnostic accuracies of the κFLC index, κIgG index, CSF κFLC/IgG ratio, and isolated CSF κFLC (iCSF-κFLC) between two reference centers using different methods., Methods: Paired serum and CSF samples were analyzed for κFLC and albumin concentrations by Freelite ® -Optilite (Sint-Jan Bruges hospital) and N Latex ® -BNII (Ghent University hospital). Diagnostic performance to differentiate MS from controls was assessed using ROC curve analysis., Results: A total of 263 participants were included (MS, n = 80). Optimal diagnostic cutoff values for the κFLC index (Freelite ® -Optilite: 7.7; N Latex ® -BNII: 4.71), κIgG index (Freelite ® -Optilite: 14.15, N Latex ® -BNII: 12.19), and CSF κFLC/IgG ratio (Freelite ® -Optilite: 2.27; N Latex ® -BNII: 1.44) differed between the two methods. Sensitivities related to optimal cutoff values were 89.9% (Freelite ® -Optilite) versus 94.6% (N Latex ® -BNII) for the κFLC index, 91% (Freelite ® -Optilite) versus 92.2% (N Latex ® -BNII) for the κIgG index, and 81.3% (Freelite ® -Optilite) versus 91.4% (N Latex ® -BNII) for the CSF κFLC/IgG ratio. However, for iCSF-κFLC, optimal diagnostic cutoff values (0.36 mg/L) and related specificities (81.8%) were identical with a related diagnostic sensitivity of 89.9% for Freelite ® -Optilite and 90.5% for N Latex ® -BNII. The diagnostic performance of the κFLC index [area under the curve (AUC) Freelite ® -Optilite: 0.924; N Latex ® -BNII: 0.962] and κIgG index (AUC Freelite ® -Optilite: 0.929; N Latex ® -BNII: 0.961) was superior compared to CSF oligoclonal bands (AUC: 0.898, sensitivity: 83.8%, specificity: 95.9%)., Conclusions: The κFLC index and the κIgG index seem to be excellent markers for identifying MS, irrespective of the method used for κFLC quantification. Based on the AUC, they appear to be the measures of choice. For all measures, optimal cutoff values differed between methods except for iCSF-κFLC. iCSF-κFLC might therefore serve as a method-independent, more cost-efficient, initial screening measure for MS. These findings are particularly relevant for clinical practice given the potential future implementation of intrathecal κFLC synthesis in MS diagnostic criteria and for future multicentre studies pooling data on κFLC measures., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Dekeyser, De Kesel, Cambron, Vanopdenbosch, Van Hijfte, Vercammen and Laureys.)

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.

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 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.)

Objective: To determine the association between lifestyle risk factors with 1/ the Multiple Sclerosis Severity Score (MSSS) and 2/ ongoing subclinical brain damage in non-active MS patients on high-efficacy treatment., Methods: Cross-sectional study in persons with Multiple Sclerosis (PwMS) investigating lifestyle factors including cognitive reserve (CR), physical activity (PA), smoking status, alcohol use, dietary habits, body mass index (BMI), blood pressure (BP) and cholesterol ratio. Data were collected through validated questionnaires, clinical and laboratory examination. Serum Neurofilament light chain (sNfL) levels were used as a proxy for ongoing brain damage in a subgroup of persons with non-active MS on high-efficacy treatment. Multiple regression analysis (MRA) models explored the relationship between lifestyle factors with the MSSS score and sNfL., Results: 351 PwMS were included (43.04 ± 11.77 years, 69.8% female). Higher CR and PA were associated with a lower MSSS; overweight or obesity and higher systolic BP with a higher MSSS. The MRA model explained 22.2% of the variance for MSSS (R².255, adjusted R².222). Higher BMI and BP were related to lower sNfL. Twenty-3% (R².279, adjusted R².230) of the variance was explained in the MRA model for sNfL., Conclusion: Our study suggests an association between a 'brain healthy lifestyle' with disability progression in MS. A cognitive and physical active lifestyle alongside a normal body weight and blood pressure may help to prevent future disability in MS. Longitudinal and interventional research is necessary to gain insight in the causal pathway of these risk factors in preventing disability progression in MS., (Copyright © 2022. Published by Elsevier B.V.)

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

Background: Increasingly, people with relapsing-remitting multiple sclerosis (RRMS) are switched to highly effective disease-modifying therapies (DMTs) such as ocrelizumab., Objective: To determine predictors of relapse and disability progression when switching from another DMT to ocrelizumab., Methods: Patients with RRMS who switched to ocrelizumab were identified from the MSBase Registry and grouped by prior disease-modifying therapy (pDMT; interferon-β/glatiramer acetate, dimethyl fumarate, teriflunomide, fingolimod or natalizumab) and washout duration (<1 month, 1-2 months or 2-6 months). Survival analyses including multivariable Cox proportional hazard regression models were used to identify predictors of on-ocrelizumab relapse within 1 year, and 6-month confirmed disability progression (CDP)., Results: After adjustment, relapse hazard when switching from fingolimod was greater than other pDMTs, but only in the first 3 months of ocrelizumab therapy (hazard ratio (HR) = 3.98, 95% confidence interval (CI) = 1.57-11.11, p  = 0.004). The adjusted hazard for CDP was significantly higher with longer washout (2-6 m compared to <1 m: HR = 9.57, 95% CI = 1.92-47.64, p  = 0.006)., Conclusion: The risk of disability worsening during switch to ocrelizumab is reduced by short treatment gaps. Patients who cease fingolimod are at heightened relapse risk in the first 3 months on ocrelizumab. Prospective evaluation of strategies such as washout reduction may help optimise this switch.

Background and Purpose: Alemtuzumab, a monoclonal CD52 antibody, is a high-efficacy disease-modifying-therapy in relapsing-remitting multiple sclerosis (RRMS). Recently, intracerebral hemorrhage (ICH) was reported as a possible treatment-related adverse event. Arterial hypertension during infusion was suggested as a potential cause, although platelet or endothelial dysfunction may also contribute. This study aimed to screen for occult hemorrhagic cerebral lesions after alemtuzumab treatment and to further elucidate risk factors., Methods: We included 30 RRMS patients who received alemtuzumab treatment at Ghent University Hospital or Sint-Jan Bruges Hospital. Retrospective data concerning vital signs, adverse effects and thrombocyte levels during treatment were collected. The occurrence of occult intracranial hemorrhagic lesions was assessed by magnetic resonance imaging with susceptibility-weighted imaging (SWI)., Results: The mean (standard deviation [SD]) systolic blood pressure (SBP) during the morning, afternoon and evening was 120 (3.38) mmHg during first administration and 114 (4.40) mmHg during second administration (N = 13). There was no significant increase in SBP when comparing morning, afternoon and evening per day, nor was there a significant difference in daily mean SBP between consecutive administration days. Thrombocyte count during treatment cycles ranged between 107 × 10 9 /L and 398 × 10 9 /L, with a mean (SD) absolute reduction of 59.3 × 10 9 /L (50.65) or a mean (SD) relative reduction of 25.0 (12.84)% (N = 20). No patient had ICH, nor did SWI show any cerebral microbleeds or other hemorrhagic lesions post-treatment (N = 23)., Conclusions: In our patient population, alemtuzumab treatment was not associated with arterial hypertension, ICH or occult microbleeds. Possible differences in administration regimen (ambulatory vs. in-hospital setting) and patient population (cardiovascular risk) might explain an increased risk in different populations., (© 2021 European Academy of Neurology.)