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With evolving diagnostic criteria and the advent of new oral and parenteral therapies for Multiple Sclerosis (MS), most current diagnostic and treatment algorithms need revision and updating. The diagnosis of MS relies on incorporating clinical and paraclinical findings to prove dissemination in space and time and exclude alternative diseases that can explain the findings at hand. The differential diagnostic workup should be guided by clinical and laboratory red flags to avoid unnecessary tests. Appropriate selection of MS therapies is critical to maximize patient benefit. The current guidelines review the current diagnostic criteria for MS and the scientific evidence supporting treatment of acute relapses, radiologically isolated syndrome, clinically isolated syndrome, relapsing remitting MS, progressive MS, pediatric cases and pregnant women. The purpose of these guidelines is to provide practical recommendations and algorithms for the diagnosis and treatment of MS based on current scientific evidence and clinical experience., Competing Interests: Declaration of competing interest The authors received honoraria from Biologix (the distributor for Biogen Idec across the Middle East and North Africa region) for serving on their advisory board and from other pharmaceutical companies including Novartis, GSK, Bayer, Merck, Sanofi and Roche. The manuscript represents the views and opinions of the members involved in the development of the guidelines. There is no industrial or pharmaceutical support or bias in the selection of the members or the recommendations reached. This effort was sponsored and carried out under the supervision of MENACTRIMS (The Middle East and North Africa Committee for Treatment and Research In Multiple Sclerosis)., (Copyright © 2024 Elsevier B.V. All rights reserved.)

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

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: 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: Knowledge about progressive Multiple Sclerosis (MS) is mainly based on Caucasian studies. In our North-African context, MS exhibits particular characteristics that are mainly related to a more severe phenotype. Given the limited data available, there is an imminent need to characterize progressive MS in our latitudes., Objective: To describe the specificities of progressive MS and identify the inherent clinical predictors of disability accrual with a Tunisian cohort., Methods: A retrospective, hospital-based study was conducted in the department of neurology of Razi hospital. Patients, who had been diagnosed with MS, were divided into relapsing MS (RRMS), secondary progressive MS (SPMS) and primary progressive MS (PPMS). Epidemiological, clinical and paraclinical data were compared among the three groups., Results: Of the 504 patients, a progressive MS was described among 115 patients. This percentage of (22.8%) is divided into 13.9% SPMS and 8.9% PPMS. During the first clinical attack, motor symptoms have revealed to be predominant during PPMS (91.1%). For SPMS onset, the median time was 10 years, and was significantly delayed for patients with visual onset or full recovery from the first relapse. Patients with progressive MS exhibited a more rapid disability accumulation., Conclusion: Compared to Caucasians, Tunisians exhibited a faster rate of conversion to SPMS. According to our natural progressive MS history, early clinical features are predictors of MS disability accrual., (Copyright © 2021. Published by Elsevier B.V.)