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Hala Darwish,1 Pia Zeinoun,2 Husam Ghusn,3,4 Brigitte Khoury,2 Hani Tamim,5 Samia J Khoury6 1Hariri School of Nursing, Faculty of Medicine, American University of Beirut, Beirut, Lebanon; 2Psychiatry Department, Faculty of Medicine, American University of Beirut, Beirut, Lebanon; 3Internal Medicine Department, Faculty of Medicine, American University of Beirut, Beirut, Lebanon; 4Geriatrics Department, Ain Wazein Hospital, El Chouf, Lebanon; 5Clinical Research Institute, Faculty of Medicine, American University of Beirut, Beirut, Lebanon; 6Neurology Department, Faculty of Medicine, American University of Beirut, Beirut, Lebanon Background: Vitamin D is an endogenous hormone known to regulate calcium levels in the body and plays a role in cognitive performance. Studies have shown an association between vitamin D deficiency and cognitive impairment in older adults. Lebanon has a high 25-hydroxyvitamin D (25(OH)D) deficiency prevalence across all age groups. Methods: In this cross-sectional study, we explored the cognitive performance and serum 25(OH)D levels using an electrochemoluminescent immunoassay in 254 older (>60 years) as well as younger (30–60 years) adults. Subjects’ characteristics, including age, years of education, wearing of veil, alcohol consumption, smoking, and physical exercise, were collected. Participants were screened for depression prior to cognitive screening using the Montreal Cognitive Assessment Arabic version. Visuospatial memory was tested using the Rey Complex Figure Test and Recognition Trial, and speed of processing was assessed using the Symbol Digit Modalities test. Results: Pearson’s correlation and stepwise linear regression analyses showed that a low vitamin D level was associated with greater risk of cognitive impairment in older as well as younger adults. Conclusion: These findings suggest that correction of vitamin D needs to be explored as an intervention to prevent cognitive impairment. Prospective longitudinal studies are needed to ascertain the effect of such interventions. Keywords: cognitive function, aging, neuro-psychological function

Mucosal and systemic administrations of high dose antigens induce long-lasting peripheral T cell tolerance. We and others have shown that high dose peripheral T cell tolerance is mediated by anergy or deletion and is preceded by T cell activation. Co-stimulatory molecules B7-1 (CD80)IB7-2 (CD86) and their counter-receptors CD28/CTLA-4 play pivotal roles in T cell activation and immune regulation. In the present study, we examined the roles of the B7 co-stimulation pathway in the generation of high dose peripheral T cell tolerance. We found that blocking B7:CD28/CTLA-4 interaction at the time of tolerance induction partially prevented T cell tolerance, whereas selective blockade of B7:CTLA-4 interaction completely abrogated peripheral T cell tolerance induced by either oral or i.p. antigens. These results suggest that CTLA-4-mediated feedback regulation plays a crucial role in the induction of high dose peripheral T cell tolerance. [ABSTRACT FROM PUBLISHER]

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

Background: Neuromyelitis optica spectrum disorder (NMOSD) can be categorised into aquaporin-4 antibody (AQP4-IgG) NMOSD or seronegative NMOSD. While our knowledge of AQP4-IgG NMOSD has evolved significantly in the past decade, seronegative NMOSD remains less understood. This study aimed to evaluate the predictors of relapses and treatment responses in AQP4-IgG NMOSD and seronegative NMOSD., Methods: This was a multicentre, international, retrospective cohort study using the MSBase registry. Recurrent relapse risk was assessed using an Andersen-Gill model and risk of first relapse was evaluated using a Cox proportional hazards model. Covariates that putatively influence relapse risk included demographic factors, clinical characteristics and immunosuppressive therapies; the latter was assessed as a time-varying covariate., Results: A total of 398 patients (246 AQP4-IgG NMOSD and 152 seronegative NMOSD) were included. The AQP4-IgG NMOSD and seronegative NMOSD patients did not significantly differ by age at disease onset, ethnicity or annualised relapse rate. Both low-efficacy and high-efficacy immunosuppressive therapies were associated with significant reductions in recurrent relapse risk, with notably greater protection conferred by high-efficacy therapies in both AQP4-IgG NMOSD (HR 0.27, 95% CI 0.15 to 0.49, p<0.001) and seronegative NMOSD (HR 0.21, 95% CI 0.08 to 0.51, p<0.001). Longer disease duration (HR 0.97, 95% CI 0.95 to 0.99, p<0.001) and male sex (HR 0.52, 95% CI 0.34 to 0.84, p=0.007) were additional protective variables in reducing the recurrent relapse risk for the AQP4-IgG NMOSD group., Conclusion: Although further studies are needed to improve our understanding of seronegative NMOSD, our findings underscore the importance of aggressive treatment with high-efficacy immunotherapies in both NMOSD subtypes, regardless of serostatus., Competing Interests: Competing interests: The author(s) would like to disclose the following. PSiriratnam has received travel support from Novartis and Biogen; AvdW has received travel support and served on advisory boards for Novartis, Biogen, Merck Serono, Roche and Teva, she receives grant support from the National Health and Medical Research Council of Australia; HB served on scientific advisory boards for Biogen, Novartis and Sanofi-Aventis and received conference travel support from Novartis, Biogen and Sanofi Aventis, he serves on steering committees for trials conducted by Biogen and Novartis and received research support from Merck, Novartis and Biogen, Medical Research Council and MS Research Australia; YCF has received travel support from Roche and Biogen, he receives grant support from Australian National Health Medical Research Council, Australia and New Zealand Association of Neurologists, AVANT foundation and MS Research Australia; WZY has received speaker honoraria from Merck and Novartis; CZ receives fellowship from the Trish Multiple Sclerosis Research Foundation; VJ receives fellowship and research support from the National Health and Medical Research Council of Australia, she also receives research grant support form F.Hoffmann La-Roche and the International Progressive MS Alliance; SH receives research support from academic entity - National Institute for Health Research (NIHR304529): Research funding; MM has served on advisory board for Merck, and Novartis and has received speaker honoraria from Merck, Biogen and Novartis, her institution receives funding from Merck, Australian National Health; 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; SJK received compensation for scientific advisory board activity from Merck and Roche, and received compensation for serving on the IDMC for Biogen; TC received speaker honoraria/conference travel support from Biogen, Merck, Novartis, Roche, Sanofi-Aventis and Teva; BW received honoraria for acting as a member of Scientific Advisory Boards/Consultancy for Alexion, Almirall, Biogen, Celgene/BMS, Merck, Janssen, Novartis, Roche, Sandoz, Sanofi-Genzyme and speaker honoraria and travel support from Biogen, Celgene/BMS, Merck, Novartis, Roche, Sanofi-Genzyme, research and/or patient support grants from Biogen, Janssen, Merck, Sanofi-Genzyme, Roche, Honoraria and grants were paid to UZA/UZA Foundation, further, B.W. received research funding from FWO-TBM, Belgian Charcot Foundation, Start2Cure Foundation, Queen Elisabeth Medical Foundation for Neurosciences and the National MS Society USA; PN received speaker honoraria and consultant fees from Biogen Idec, Novartis, Merck, Roche, Jannsen, Astra Zeneca and financial support for research activities from Roche and Merck, the work of PN was supported by Ministry of Health of the Czech Republic, grant nr. NU23-05-00462; AA received speaker honoraria from Novartis and Alexion; AA-A received personal compensation for serving as a Scientific Advisory or speaker/moderator for Novartis, Biogen, Roche, Sanofi-Genzyme, and Merck; BY received honoraria as a speaker and member of scientific advisory boards from Sanofi, Bayer, Biogen, Merck, Janssen, Novartis, Roche and Aspen; GL received travel and/or consultancy compensation from Sanofi-Genzyme, Roche, Teva, Merck, Novartis, Celgene, Biogen; FP received personal compensation for serving on advisory board by Almirall, Alexion, Biogen, Bristol, Janssen, Merck, Novartis and Roche, he further received research grant by Alexion, Almirall, Biogen, Bristol, Merck, Novartis and Roche and by FISM, Reload Association (Onlus), Italian Health Minister and University of Catania. Magdolna Simo received speaker honoraria from Novartis, Biogen, Bayer Schering, Sanofi, Merck, Roche, congress/travel compensation from Teva, Biogen, Merck, Bayer Schering Novartis, Roche; MF received travel and meeting attendance support from Novartis, Biogen, Roche, Sanofi-Genzyme and Merck; ASoysal received travel and meeting attendance support from Novartis, Biogen, Roche, Merck, Bristol, Sanofi-Genzyme, Almirall, Piam; PAM received honoraria and consulting fees from Novartis, Bayer Schering and Sanofi and travel grants from Novartis, Biogen and Bayer Schering; RA received honoraria as a speaker and for serving on scientific advisory boards from Bayer, Biogen, GSK, Merck, Novartis, Roche and Sanofi-Genzyme; 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; JLS received 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., (© Author(s) (or their employer(s)) 2024. No commercial re-use. See rights and permissions. Published by BMJ.)

Spectral domain-optical coherence tomography plays a crucial role in the early detection and monitoring of multiple sclerosis (MS) pathophysiology. We aimed to quantify differences in retinal layer measures among different groups of MS and explored different variables that correlate with retinal measures. This study was reported according PRISMA guidelines. A comprehensive search was done across PubMed, Embase, and Google Scholar. The mean difference in thickness of retinal layers and macular volume was assessed. Meta-regression was done to assess the sources of heterogeneity. A total of 100 articles were included in the meta-analyses. The peripapillary retinal nerve fiber layer (pRNFL) thickness significantly decreased in the MSON (MD: -16.44, P < 0.001), MSNON (MD: -6.97, P < 0.001), and PMS (MD: -11.35, P < 0.001) versus HC. The macular RNFL was lower among the MSON (MD: -6.24, P = 0.013) and MSNON (MD: -3.84, P <0.001) versus HC. Macular ganglion cell layer and inner plexiform layer (GCIPL) was thinner among MSON (MD: -14.83, P <0.001), MSNON (MD: -6.38, P < 0.001), and PMS (MD: -11.52, P < 0.001) compared with control eyes. Inner nuclear layer (INL) was higher in the MSON (MD: 0.49, P < 0.001) versus HC. Outer nuclear layer (ONL) thickness significantly lower in the MSNON (MD: -1.15, P = 0.019) versus HC. Meta-regression showed that disease duration, age, EDSS score, and percentage of patients taking DMT are all negatively correlated with pRNFL and GCIPL thickness; however, female gender was correlated with less atrophy. As conclusion, the study highlights substantial thinning in the pRNFL and macular GCIPL between MS versus controls. INL as valuable parameter for capturing inflammatory disease activity., (© 2024 The Author(s). Annals of Clinical and Translational Neurology published by Wiley Periodicals LLC on behalf of American Neurological Association.)

Background: The COVID-19 pandemic raised concern amongst clinicians that disease-modifying therapies (DMT), particularly anti-CD20 monoclonal antibodies (mAb) and fingolimod, could worsen COVID-19 in people with multiple sclerosis (pwMS). This study aimed to examine DMT prescribing trends pre- and post-pandemic onset., Methods: A multi-centre longitudinal study with 8,771 participants from MSBase was conducted. Two time periods were defined: pre-pandemic (March 11 2018-March 10 2020) and post-pandemic onset (March 11 2020-11 March 2022). The association between time and prescribing trends was analysed using multivariable mixed-effects logistic regression. DMT initiation refers to first initiation of any DMT, whilst DMT switches indicate changing regimen within 6 months of last use., Results: Post-pandemic onset, there was a significant increase in DMT initiation/switching to natalizumab and cladribine [(Natalizumab-initiation: OR 1.72, 95% CI 1.39-2.13; switching: OR 1.66, 95% CI 1.40-1.98), (Cladribine-initiation: OR 1.43, 95% CI 1.09-1.87; switching: OR 1.67, 95% CI 1.41-1.98)]. Anti-CD20mAb initiation/switching decreased in the year of the pandemic, but recovered in the second year, such that overall odds increased slightly post-pandemic (initiation: OR 1.26, 95% CI 1.06-1.49; Switching: OR 1.15, 95% CI 1.02-1.29. Initiation/switching of fingolimod, interferon-beta, and alemtuzumab significantly decreased [(Fingolimod-initiation: OR 0.55, 95% CI 0.41-0.73; switching: OR 0.49, 95% CI 0.41-0.58), (Interferon-gamma-initiation: OR 0.48, 95% CI 0.41-0.57; switching: OR 0.78, 95% CI 0.62-0.99), (Alemtuzumab-initiation: OR 0.27, 95% CI 0.15-0.48; switching: OR 0.27, 95% CI 0.17-0.44)]., Conclusions: Post-pandemic onset, clinicians preferentially prescribed natalizumab and cladribine over anti-CD20 mAbs and fingolimod, likely to preserve efficacy but reduce perceived immunosuppressive risks. This could have implications for disease progression in pwMS. Our findings highlight the significance of equitable DMT access globally, and the importance of evidence-based decision-making in global health challenges., (© 2024. The Author(s).)

Background: Disability progression is a key milestone in the disease evolution of people with multiple sclerosis (PwMS). Prediction models of the probability of disability progression have not yet reached the level of trust needed to be adopted in the clinic. A common benchmark to assess model development in multiple sclerosis is also currently lacking., Methods: Data of adult PwMS with a follow-up of at least three years from 146 MS centers, spread over 40 countries and collected by the MSBase consortium was used. With basic inclusion criteria for quality requirements, it represents a total of 15, 240 PwMS. External validation was performed and repeated five times to assess the significance of the results. Transparent Reporting for Individual Prognosis Or Diagnosis (TRIPOD) guidelines were followed. Confirmed disability progression after two years was predicted, with a confirmation window of six months. Only routinely collected variables were used such as the expanded disability status scale, treatment, relapse information, and MS course. To learn the probability of disability progression, state-of-the-art machine learning models were investigated. The discrimination performance of the models is evaluated with the area under the receiver operator curve (ROC-AUC) and under the precision recall curve (AUC-PR), and their calibration via the Brier score and the expected calibration error. All our preprocessing and model code are available at https://gitlab.com/edebrouwer/ms&#95;benchmark, making this task an ideal benchmark for predicting disability progression in MS., Findings: Machine learning models achieved a ROC-AUC of 0⋅71 ± 0⋅01, an AUC-PR of 0⋅26 ± 0⋅02, a Brier score of 0⋅1 ± 0⋅01 and an expected calibration error of 0⋅07 ± 0⋅04. The history of disability progression was identified as being more predictive for future disability progression than the treatment or relapses history., Conclusions: Good discrimination and calibration performance on an external validation set is achieved, using only routinely collected variables. This suggests machine-learning models can reliably inform clinicians about the future occurrence of progression and are mature for a clinical impact study., Competing Interests: The authors declare no competing non-financial interests but the following competing financial interests: - Dana Horakova received speaker honoraria and consulting fees from Biogen, Merck, Teva, Roche, Sanofi Genzyme, and Novartis, as well as support for research activities from Biogen and Czech Minsitry of Education [project Progres Q27/LF1]. - Francesco Patti received speaker honoraria and advisory board fees from Almirall, Bayer, Biogen, Celgene, Merck, Novartis, Roche, Sanofi-Genzyme and TEVA. He received research funding from Biogen, Merck, FISM (Fondazione Italiana Sclerosi Multipla), Reload Onlus Association and University of Catania. - Guillermo Izquierdo received speaking honoraria from Biogen, Novartis, Sanofi, Merck, Roche, Almirall and Teva. - Sara Eichau received speaker honoraria and consultant fees from Biogen Idec, Novartis, Merck, Bayer, Sanofi Genzyme, Roche and Teva. - Marc Girard received consulting fees from Teva Canada Innovation, Biogen, Novartis and Genzyme Sanofi; lecture payments from Teva Canada Innovation, Novartis and EMD. He has also received a research grant from Canadian Institutes of Health Research. - Alessandra Lugaresi has served as a Biogen, Bristol Myers Squibb, Merck Serono, Novartis, Roche, Sanofi/ Genzyme and Teva Advisory Board Member. She received congress and travel/accommodation expense compensations or speaker honoraria from Biogen, Merck, Mylan, Novartis, Roche, Sanofi/Genzyme, Teva and Fondazione Italiana Sclerosi Multipla (FISM). Her institutions received research grants from Novartis and Sanofi Genzyme. - Pierre Grammond has served in advisory boards for Novartis, EMD Serono, Roche, Biogen idec, Sanofi Genzyme, Pendopharm and has received grant support from Genzyme and Roche, has received research grants for his institution from Biogen idec, Sanofi Genzyme, EMD Serono. - Tomas Kalincik served on scientific advisory boards for BMS, Roche, Janssen, Sanofi Genzyme, Novartis, Merck and Biogen, steering committee for Brain Atrophy Initiative by Sanofi Genzyme, received conference travel support and/or speaker honoraria from WebMD Global, Eisai, Novartis, Biogen, Sanofi-Genzyme, Teva, BioCSL and Merck and received research or educational event support from Biogen, Novartis, Genzyme, Roche, Celgene and Merck. - Raed Alroughani received honoraria as a speaker and for serving on scientific advisory boards from Bayer, Biogen, GSK, Merck, Novartis, Roche and Sanofi-Genzyme. - Francois Grand’Maison received honoraria or research funding from Biogen, Genzyme, Novartis, Teva Neurosciences, Mitsubishi and ONO Pharmaceuticals. - Murat Terzi received travel grants from Novartis, Bayer-Schering, Merck and Teva; has participated in clinical trials by Sanofi Aventis, Roche and Novartis. - Jeannette Lechner-Scott travel compensation from Novartis, Biogen, Roche and Merck. Her institution receives the honoraria for talks and advisory board commitment as well as research grants from Biogen, Merck, Roche, TEVA and Novartis. - Samia J. Khoury received compensation for participation in the Novartis Maestro program. - Vincent van Pesch has received travel grants from Merck, Biogen, Sanofi, Bristol Myers Squibb, Almirall and Roche; his institution receives honoraria for consultancy and lectures and research grants from Roche, Biogen, Sanofi, Merck, Bristol Myers Squibb, Janssen, Almirall and Novartis Pharma. - Radek Ampapa received conference travel support from Novartis, Teva, Biogen, Bayer and Merck and has participated in a clinical trials by Biogen, Novartis, Teva and Actelion. - Daniele Spitaleri received honoraria as a consultant on scientific advisory boards by Bayer-Schering, Novartis and Sanofi-Aventis and compensation for travel from Novartis, Biogen, Sanofi Aventis, Teva and Merck. - Claudio Solaro served on scientific advisory boards for Merck, Genzyme, Almirall, and Biogen; received honoraria and travel grants from Sanofi Aventis, Novartis, Biogen, Merck, Genzyme and Teva. - Davide Maimone served on scientific advisory boards for Bayer, Biogen, Merck, Sanofi-Genzyme, Novartis, Roche, and Almirall; received honoraria and travel grants from Sanofi Genzyme, Novartis, Biogen, Merck, and Roche. - Gerardo Iuliano (retired - no PI successor but has approved ongoing use of data) had travel/accommodations/meeting expenses funded by Bayer Schering, Biogen, Merck, Novartis, Sanofi Aventis, and Teva. - Bart Van Wijmeersch received research and travel grants, honoraria for MS-Expert advisor and Speaker fees from Bayer-Schering, Biogen, Sanofi Genzyme, Merck, Novartis, Roche and Teva. - Tamara Castillo Triviño received speaking/consulting fees and/or travel funding from Bayer, Biogen, Merck, Novartis, Roche, Sanofi-Genzyme and Teva. - Jose Luis Sanchez-Menoyo accepted travel compensation from Novartis, Merck and Biogen, speaking honoraria from Biogen, Novartis, Sanofi, Merck, Almirall, Bayer and Teva and has participated in clinical trials by Biogen, Merck and Roche - Guy Laureys received travel and/or consultancy compensation from Sanofi-Genzyme, Roche, Teva, Merck, Novartis, Celgene, Biogen. - Anneke van der Walt served on advisory boards and receives unrestricted research grants from Novartis, Biogen, Merck and Roche She has received speaker’s honoraria and travel support from Novartis, Roche, and Merck. She receives grant support from the National Health and Medical Research Council of Australia and MS Research Australia. - Jiwon Oh has received research funding from the MS Society of Canada, National MS Society, Brain Canada, Biogen, Roche, EMD Serono (an affiliate of Merck KGaA); and personal compensation for consulting or speaking from Alexion, Biogen, Celgene (BMS), EMD Serono (an affiliate of Merck KGaA), Novartis, Roche, and Sanofi-Genzyme. - Ayse Altintas received speaker honoraria from Merck, Alexion,; received travel and registration grants from Merck, Biogen - Gen Pharma, Roche, Sanofi-Genzyme. - Yara Fragoso received honoraria as a consultant on scientific advisory boards by Novartis, Teva, Roche and Sanofi-Aventis and compensation for travel from Novartis, Biogen, Sanofi Aventis, Teva, Roche and Merck. - Tunde Csepany received speaker honoraria/ conference travel support from Bayer Schering, Biogen, Merck, Novartis, Roche, Sanofi-Aventis and Teva. - Suzanne Hodgkinson received honoraria and consulting fees from Novartis, Bayer Schering and Sanofi, and travel grants from Novartis, Biogen Idec and Bayer Schering. - Norma Deri received funding from Bayer, Merck, Biogen, Genzyme and Novartis. - Bruce Taylor received funding for travel and speaker honoraria from Bayer Schering Pharma, CSL Australia, Biogen and Novartis, and has served on advisory boards for Biogen, Novartis, Roche and CSL Australia. - Fraser Moore participated in clinical trials sponsored by EMD Serono and Novartis. - Orla Gray received honoraria as consultant on scientific advisory boards for Genzyme, Biogen, Merck, Roche and Novartis; has received travel grants from Biogen, Merck, Roche and Novartis; has participated in clinical trials by Biogen and Merck. - Csilla Rozsa received speaker honoraria from Bayer Schering, Novartis and Biogen, congress and travel expense compensations from Biogen, Teva, Merck and Bayer Schering. - Allan Kermode received speaker honoraria and scientific advisory board fees from Bayer, BioCSL, Biogen, Genzyme, Innate Immunotherapeutics, Merck, Novartis, Sanofi, Sanofi-Aventis, and Teva. - Magdolna Simo received speaker honoraria from Novartis, Biogen, Bayer Schering; congress/travel compensation from Teva, Biogen, Merck, Bayer Schering. - Todd Hardy has received speaking fees or received honoraria for serving on advisory boards for Biogen, Merck, Teva, Novartis, Roche, Bristol-Myers Squibb and Sanofi-Genzyme, is Co-Editor of Advances in Clinical Neurosciences and Rehabilitation, and serves on the editorial board of Journal of Neuroimmunology and Frontiers in Neurology. - Nikolaos Grigoriadis received honoraria, consultancy/lecture fees, travel support and research grants from Biogen Idec, Biologix, Novartis, TEVA, Bayer, Merck Serono, Genesis Pharma, Sanofi – Genzyme, ROCHE, Cellgene, ELPEN and research grants from Hellenic Ministry of Development., (Copyright: © 2024 De Brouwer et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: To mimic as closely as possible a randomised controlled trial (RCT) and calibrate the real-world evidence (RWE) studies against a known treatment effect would be helpful to understand if RWE can support causal conclusions in selected circumstances. The aim was to emulate the TRANSFORMS trial comparing Fingolimod (FTY) versus intramuscular interferon β-1a (IFN) using observational data., Methods: We extracted from the MSBase registry all the patients with relapsing-remitting multiple sclerosis (RRMS) collected in the period 2011-2021 who received IFN or FTY (0.5 mg) and with the same inclusion and exclusion criteria of the TRANSFORMS RCT. The primary endpoint was the annualised relapse rate (ARR) over 12 months. Patients were 1:1 propensity-score (PS) matched. Relapse-rate ratio (RR) was calculated by mean of a negative binomial regression., Results: A total of 4376 patients with RRMS (1140 in IFN and 3236 in FTY) were selected. After PS, 856 patients in each group were matched. The ARR was 0.45 in IFN and 0.25 in FTY with a significant difference between the two groups (RR: 0.55, 95% CI: 0.45 to 0.68; p<0.001). The result of the emulation was very similar and fell within the 95% CI of that observed in the RCT (RR: 0.49, 95% CI: 0.37 to 0.64; p<0.001) with a standardised difference of 0.66 (p=0.51)., Conclusions: By applying the same inclusion and exclusion criteria used in the RCT and employing appropriate methodology, we successfully replicated the RCT results with only minor discrepancies. Also, even if the confounding bias cannot be fully eliminated, conducting a rigorous target trial emulation could still yield valuable insights for comparative effectiveness research., Competing Interests: Competing interests: MP, SO, BY, RK, AYS have nothing to disclose; AS received speaker’s honoraria from Chiesi and grant from MSBase outside from this work. TK 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. 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 Minsitry of Education [project Progres Q27/LF1]. 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; has been supported by the Czech Ministry of Educaon research project PROGRES Q27/LF1. RA received honoraria as a speaker and for serving on scientific advisory boards from Bayer, Biogen, GSK, Merck, Novartis, Roche and Sanofi-Genzyme. JK received speaker fees, research support, travel support, and/or advisory boards Swiss Multiple Sclerosis Society, SNSF, University of Basel, Progressive Multiple Sclerosis Alliance, Bayer, Biogen, Celgene, Merck, Novartis, Octave Bioscience, Roche, Sanofi. FP served an advisory board Alexion, Almirall, Bayer, Biogen, Bristol Meyers&Squibb, Merck, Novartis and Roche; he also received personal fee for speaking activities; he also received research grants by Biogen, Merck, Roche, FISM, Reload Onlus and MIUR Ministero Italiano della Ricerca e della Università. GI received speaking honoraria from Biogen, Novartis, Sanofi, Merck, Roche, Almirall and Teva. SJK received compensation for scientific advisory board activity from Merck and Roche and for serving on IDMC for Biogen. SE received speaker honoraria and consultant fees from Biogen Idec, Novartis, Merck, Bayer, Sanofi Genzyme, Roche and Teva. 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. 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. 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. AV served on advisory boards for Novartis, Biogen, Merck and Roche and NervGen. She received unrestricted research grants from Novartis, Biogen, Merck and Roche. She is currently a co-Principal investigator on a co-sponsored observational study with Roche, evaluating a Roche-developed smartphone app, Floodlight-MS. She has received speaker’s honoraria and travel support from Novartis, Roche, Biogen and Merck. She serves as the Chief operating Officer of the MSBase Foundation (not for profit). Her primary research support is from the National Health and Medical Research Council of Australia and MS Research Australia. MPS received consulting fees from Roche, Biogen, Merck, Novartis, Sanofi, Celgene, Immunic, Geneuro, GSK, Medday; received payment or honoraria for lectures, presentations, speakers’ bureaus, manuscript writing or educational events from Roche, Biogen Merck, Novartis, Sanofi, Celgene; participated on a Data Safety Monitoring Board or Advisory Board for Roche, Sanofi, Novartis, Merck., (© Author(s) (or their employer(s)) 2024. No commercial re-use. See rights and permissions. Published by BMJ.)

Objective: This study assessed the Health-Related Quality of Life (HRQoL) and utilities of Multiple Sclerosis (MS) patients in Lebanon using generic and MS-specific QoL instruments, categorized by disease severity, and explored factors associated with HRQoL., Methods: This was a cross-sectional, retrospective HRQoL study collecting data through face-to-face interviews using the EQ-5D-5 L and the Multiple Sclerosis International Quality of Life (MusiQoL) questionnaires. We enrolled Lebanese patients aged ≥18 years, diagnosed with MS for >6 months. Patients were categorized by disease severity using the expanded disability status scale (EDSS) scores: 0-3 (mild MS), 4-6.5 (moderate MS), and 7-9 (severe MS). Bivariate and linear regression analyses were performed to study factors associated with HRQoL., Results: A total of 210 patients (mean age: 43.3 years; 65.7 % females) were included. The mean EQ-5D-5 L utility score was 0.74. This score decreased significantly with disease severity (p < 0.001 for the trend): 0.93, 0.60, and 0.32 for mild, moderate, and severe MS, respectively. The mean MusiQoL global index score was 71.33 and was significantly lower for severe MS (58.68), than for moderate (65.23) and mild (77.80), (p < 0.001 for the trend). Higher educational level, lower EDSS scores, and longer disease duration were associated significantly with a higher EQ-5D-5 L utility (R2 = 0.67), while employment, lower EDSS scores, and decrease in cognitive difficulties were associated with better MusiQoL utility (R2 = 0.46)., Conclusions: This study reveals a significant and gradual deterioration in HRQoL as MS progresses, resulting in low utility scores for patients with severe MS., Competing Interests: Declaration of competing interest The authors declare that they have no conflict or financial interests., (Copyright © 2024. Published by Elsevier B.V.)

Background and Objectives: Patients with pediatric-onset multiple sclerosis (POMS) typically experience higher levels of inflammation with more frequent relapses, and though patients with POMS usually recover from relapses better than adults, patients with POMS reach irreversible disability at a younger age than adult-onset patients. There have been few randomized, placebo-controlled clinical trials of multiple sclerosis (MS) disease-modifying therapies (DMTs) in patients with POMS, and most available data are based on observational studies of off-label use of DMTs approved for adults. We assessed the effectiveness of natalizumab compared with fingolimod using injectable platform therapies as a reference in pediatric patients in the global MSBase registry., Methods: This retrospective study included patients with POMS who initiated treatment with an injectable DMT, natalizumab, or fingolimod between January 1, 2006, and May 3, 2021. Patients were matched using inverse probability treatment weighting. The primary outcome was time to first relapse from index therapy initiation. Secondary study outcomes included annualized relapse rate; proportions of relapse-free patients at 1, 2, and 5 years; time to treatment discontinuation; and times to 24-week confirmed disability worsening and confirmed disability improvement., Results: A total of 1,218 patients with POMS were included in this analysis. Patients treated with fingolimod had a significantly lower risk of relapse than patients treated with injectable DMTs (hazard ratio [HR], 0.49; 95% confidence interval [CI], 0.29-0.83; p = 0.008). After adjustment for prior DMT experience in the unmatched sample, patients treated with natalizumab had a significantly lower risk of relapse than patients treated either with injectable DMTs (HR, 0.15; 95% CI 0.07-0.31; p < 0.001) or fingolimod (HR, 0.37; 95% CI 0.14-1.00; p = 0.049). The adjusted secondary study outcomes were generally consistent with the primary outcome or with previous observations. The findings in the inverse probability treatment weighting-adjusted patient populations were confirmed in multiple sensitivity analyses., Discussion: Our analyses of relapse risk suggest that natalizumab is more effective than fingolimod in the control of relapses in this population with high rates of new inflammatory activity, consistent with previous studies of natalizumab and fingolimod in adult-onset patients and POMS. In addition, both fingolimod and natalizumab were more effective than first-line injectable therapies., Classification of Evidence: This study provides Class II evidence that patients with POMS treated with natalizumab had a lower risk of relapse than those with fingolimod.

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).)

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: Multiple sclerosis (MS) is an autoimmune demyelinating disease that involves the central nervous system (CNS). Individuals with Multiple Sclerosis (MS) may experience difficulty adapting to their diagnosis as the unpredictable nature of the disease can be challenging to cope with., Methods: The purpose of this study is twofold. First, we have culturally adapted and analyzed the Arabic version of the Multiple Sclerosis Resiliency Scale (MSRS) psychometric properties. Second, we aimed to explore resilience in a sample of Lebanese patients with MS in the face of the chronic disease and financial hardship that Lebanon is going through to evaluate their strengths and struggles. The sample consisted of 306 participants aged between 18 and 79 diagnosed with MS for at least one year., Results: After examining criterion validity, construct validity, internal consistency, and test-retest reliability, the Arabic version of the MSRS exhibited good psychometric properties. The study also revealed that resilience increases with age and lower disability scores. Additionally, individuals with higher resilience levels displayed lower levels of depression. The research revealed that MS patients have high resilience, mainly relying on cognitive and emotional strategies, social support from family and friends, MS peer support, and spirituality., Conclusion: These findings highlight the importance of emotional coping strategies and social support in building resilience among MS patients., Competing Interests: This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors., (© 2023 The Authors. Published by Elsevier B.V.)

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.)

The widespread use of magnetic resonance imaging (MRI) has led to an increase in incidental findings in the central nervous system. Radiologically isolated syndrome (RIS) is a condition where imaging reveals lesions suggestive of demyelinating disease without any clinical episodes consistent with multiple sclerosis (MS). The prognosis for RIS patients is uncertain, with some remaining asymptomatic while others progress to MS. Several risk factors for disease progression have been identified, including male sex, younger age at diagnosis, and spinal cord lesions. This article reviews two promising biomarkers, the central vein sign (CVS) and the paramagnetic rim sign (PRS), and their potential role in the diagnosis and prognosis of MS and RIS. Both CVS and PRS have been shown to be accurate diagnostic markers in MS, with high sensitivity and specificity, and have been useful in distinguishing MS from other disorders. Further research is needed to validate these findings and determine the clinical utility of these biomarkers in routine practice., (© 2023 European Academy of Neurology.)

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.)

A central issue in regenerative medicine is understanding the mechanisms that regulate the self-renewal of endogenous stem cells in response to injury and disease. Interferons increase hematopoietic stem cells during infection by activating STAT1, but the mechanisms by which STAT1 regulates intrinsic programs in neural stem cells (NSCs) during neuroinflammation is less known. Here we explored the role of STAT1 on NSC self-renewal. We show that overexpressing Stat1 in NSCs derived from the subventricular zone (SVZ) decreases NSC self-renewal capacity while Stat1 deletion increases NSC self-renewal, neurogenesis, and oligodendrogenesis in isolated NSCs. Importantly, we find upregulation of STAT1 in NSCs in a mouse model of multiple sclerosis (MS) and an increase in pathological T cells expressing IFN-γ rather than interleukin 17 (IL-17) in the cerebrospinal fluid of affected mice. We find IFN-γ is superior to IL-17 in reducing proliferation and precipitating an abnormal NSC phenotype featuring increased STAT1 phosphorylation and Stat1 and p16 ink4a gene expression. Notably, Stat1 -/- NSCs were resistant to the effect of IFN-γ. Lastly, we identified a Stat1 -dependent gene expression profile associated with an increase in the Sox9 transcription factor, a regulator of self-renewal. Stat1 binds and transcriptionally represses Sox9 in a transcriptional luciferase assay. We conclude that Stat1 serves as an inducible checkpoint for NSC self-renewal that is upregulated during chronic brain inflammation leading to decreased self-renewal. As such, Stat1 may be a potential target to modulate for next generation therapies to prevent progression and loss of repair function in NSCs/neural progenitors in MS., 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 © 2023 Imitola, Hollingsworth, Watanabe, Olah, Elyaman, Starossom, Kivisäkk and Khoury.)

An 18-protein multiple sclerosis (MS) disease activity (DA) test was validated based on associations between algorithm scores and clinical/radiographic assessments (N = 614 serum samples; Train [n = 426; algorithm development] and Test [n = 188; evaluation] subsets). The multi-protein model was trained based on presence/absence of gadolinium-positive (Gd+) lesions and was also strongly associated with new/enlarging T2 lesions, and active versus stable disease (composite of radiographic and clinical evidence of DA) with improved performance (p < 0.05) compared to the neurofilament light single protein model. The odds of having ≥1 Gd+ lesions with a moderate/high DA score were 4.49 times that of a low DA score, and the odds of having ≥2 Gd+ lesions with a high DA score were 20.99 times that of a low/moderate DA score. The MSDA Test was clinically validated with improved performance compared to the top-performing single-protein model and can serve as a quantitative tool to enhance the care of MS patients., Competing Interests: Declaration of Competing Interest Tanuja Chitnis has received compensation for consulting from Biogen, Novartis Pharmaceuticals, Roche Genentech, and Sanofi Genzyme, and has received research support from the National Institutes of Health, National MS Society, US Department of Defense, EMD Serono, I-Mab Biopharma, Mallinckrodt ARD, Novartis Pharmaceuticals, Octave Bioscience, Inc., Roche Genentech, and Tiziana Life Sciences. This research was conducted in part with the support of the Department of Defense through the Multiple Sclerosis Research Program under Award No. W81XWH-18-1-0648 (to T. Chitnis). John Foley has received research support from Biogen, Novartis, Adamas, Octave Bioscience, Inc., Genentech, and Mallinckrodt, has received speakers' honoraria and acted as a consultant for EMD Serono, Genzyme, Novartis, Biogen, and Genentech, has equity interest in Octave Bioscience, Inc., and is the founder of InterPro Bioscience. Carolina Ionete has received research support from Biogen, Serono, Genentech, NMSS, and the Department of Defense, and received compensation for advisory board activity from Sanofi-Genzyme. Nabil K. El Ayoubi has received support to attend scientific educational courses from Novartis, Merck Serono, Sanofi, Biologix, and has received speaker honoraria for scientific presentations on Multiple Sclerosis from Biologix, Sanofi, Merck Serono, and Novartis. Shrishti Saxena, Patricia Gaitan-Walsh, Anu Paul, and Fermisk Saleh have no disclosures. Hrishikesh Lokhande has received research support from the US Department of Defense and Octave Bioscience, Inc. Howard Weiner has received research support from the Department of Defense, Genentech, Inc., National Institutes of Health, National Multiple Sclerosis Society, Novartis, and Sanofi Genzyme. He has received compensation for consulting from Genentech, Inc., IM Therapeutics, IMAB Biopharma, MedDay Pharmaceuticals, Tiziana Life Sciences, and vTv Therapeutics. Ferhan Qureshi, Anisha Keshavan, Kian Jalaleddini, and Ati Ghoreyshi are employees of Octave Bioscience, Inc. Michael J. Becich, Fatima Rubio da Costa, Victor M. Gehman, and Fujun Zhang were employees of Octave Bioscience, Inc., at the time the study was completed. Samia J. Khoury has received compensation for scientific advisory board activity from Merck and Roche and for serving on IDMC for Biogen., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

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.

Introduction: This study assessed the societal costs of multiple sclerosis (MS) in Lebanon, categorized by disease severity., Methods: This was a cross-sectional, prevalence-based, bottom-up study using a face-to-face questionnaire. Patients were stratified by disease severity using the expanded disability status scale (EDSS); EDSS scores of 0-3, 4-6.5, and 7-9 indicating respectively mild, moderate, and severe MS. All direct medical, nonmedical, and indirect costs related to reduced productivity were accounted for regardless of who bore them. Costs, collected from various sources, were presented in international US dollars (US$) using the purchasing power parity (PPP) conversion rate., Results: We included 210 Lebanese patients (mean age: 43.3 years; 65.7% females). The total annual costs per patient were PPP US$ 33,117 for 2021, 12.4 times higher than the nominal GDP per capita. Direct costs represented 52% (US$ 17,185), direct nonmedical costs 8% (US$ 2,722), and indirect costs 40% (US$ 13, 211) of the mean annual costs. The total annual costs per patient increased with disease severity and were PPP US$ 29,979, PPP US$ 36,125, PPP US$ 39,136 for mild, moderate, and severe MS, respectively., Conclusion: This study reveals the huge economic burden of MS on the Lebanese healthcare system and society.

Background: Timely initiation of disease modifying therapy is crucial for managing multiple sclerosis (MS)., Objective: We aimed to validate a previously published predictive model of individual treatment response using a non-overlapping cohort from the Middle East., Methods: We interrogated the MSBase registry for patients who were not included in the initial model development. These patients had relapsing MS or clinically isolated syndrome, a recorded date of disease onset, disability and dates of disease modifying therapy, with sufficient follow-up pre- and post-baseline. Baseline was the visit at which a new disease modifying therapy was initiated, and which served as the start of the predicted period. The original models were used to translate clinical information into three principal components and to predict probability of relapses, disability worsening or improvement, conversion to secondary progressive MS and treatment discontinuation as well as changes in the area under disability-time curve (ΔAUC). Prediction accuracy was assessed using the criteria published previously., Results: The models performed well for predicting the risk of disability worsening and improvement (accuracy: 81%-96%) and performed moderately well for predicting the risk of relapses (accuracy: 73%-91%). The predictions for ΔAUC and risk of treatment discontinuation were suboptimal (accuracy < 44%). Accuracy for predicting the risk of conversion to secondary progressive MS ranged from 50% to 98%., Conclusion: The previously published models are generalisable to patients with a broad range of baseline characteristics in different geographic regions.

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: Retinal optical coherence tomography (OCT) can differentiate definite NMOSD (dNMOSD) from multiple sclerosis (MS), but has not been evaluated in patients with a high clinical suspicion of NMOSD and not fulfilling the current consensus diagnostic criteria, referred in this paper as "potential" NMOSD (pNMOSD)., Aim: To compare the retinal OCT measurements between patients with pNMOSD, dNMOSD, MS, and reference healthy controls (HC)., Material and Methods: In this cross-sectional study, clinical and demographic characteristics, as well as OCT measurements of peripapillary retinal nerve fiber layer (pRNFL), inner nuclear layer (INL), macular retinal nerve fiber layer (mRNFL), outer nuclear layer (ONL) ganglion cell/inner plexiform layer (GCIPL), and macular volume (MV) were compared between groups. Mixed-effects regression models adjusting for within-patient inter-eye correlations, controlling for age, gender, disease duration and history of optic neuritis per eye were explored. Subgroup analyses were performed on eyes with previous optic neuritis., Results: 234 eyes (20 pNMOSD, 33 dNMOSD, 138 MS, and 43 HC) were included. Controlling for age, gender, disease duration, and history of optic neuritis per eye, pNMOSD eyes showed decreased GCIPL, pRNFL, mRNFL and MV thicknesses, similar to eyes with dNMOSD, but significantly thinner than MS and HC subjects' eyes. Similar results were obtained for the pRNFL, mRNFL, GCIPL, INL and MV thickness in the subgroup analysis exploring only eyes with history of optic neuritis (12 pNMOSD, 15 dNMOSD, and 27 MS)., Conclusion: Retinal OCT measurements in patients with pNMOSD were similar to dNMOSD, but significantly lower than patients with MS and healthy controls. This suggests that retinal OCT measures could be helpful markers supportive of NMOSD diagnosis and should be explored in larger studies as a valuable addition to the current consensus diagnostic criteria., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022. Published by Elsevier B.V.)

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

Background and Objectives: The diagnosis of secondary progressive multiple sclerosis (SPMS) is often delayed because of the lack of objective clinical tools, which increases the diagnostic uncertainty and hampers the therapeutic development in progressive multiple sclerosis (MS). Optical coherence tomography (OCT) has been proposed as a promising biomarker of progressive neurodegeneration. To explore longitudinal changes in the thicknesses of retinal layers on OCT in individuals with relapsing-remitting MS (RRMS) who converted to SPMS vs matched patients with RRMS who did not convert to SPMS. Our hypothesis is that the 2 cohorts exhibit different rates of retinal thinning., Methods: From our prospective observational cohort of patients with MS at the American University of Beirut, we selected patients with RRMS who converted to SPMS during the observation period and patients with RRMS, matched by age, disease duration, and Expanded Disability Status Scale (EDSS) at the first visit. Baseline retinal measurements were obtained using spectral domain OCT, and all patients underwent clinical and OCT evaluation every 6-12 months on average throughout the study period (mean = 4 years). Mixed-effect regression models were used to assess the annualized rates of retinal changes and the differences between the 2 groups and between converters to SPMS before and after their conversion., Results: A total of 61 participants were selected (21 SPMS and 40 RRMS). There were no differences in baseline characteristics and retinal measurements between the 2 groups. The annualized rates of thinning of all retinal layers, except for macular volume, were greater in converters before conversion compared with nonconverters by 112% for peripapillary retinal nerve fiber layer ( p = 0.008), 344% for tRNFL ( p < 0.0001), and 82% for cell-inner plexiform layer (GCIPL) ( p = 0.002). When comparing the annualized rate of thinning for the same patients with SPMS before and after conversion, no significant differences were found except for tRNFL and GCIPL with slower thinning rates postconversion (46% and 68%, respectively)., Discussion: Patients who converted to SPMS exhibited faster retinal thinning as reflected on OCT. Longitudinal assessment of retinal thinning could confirm the transition to SPMS and help with the therapeutic decision making for patients with MS with clinical suspicion of disease progression., (Copyright © 2022 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.)

Background: Early recognition of markers of faster disability worsening in paediatric-onset multiple sclerosis (MS) is a key requisite of personalised therapy for children with MS at the earliest possible time., Objective: To identify early predictors of rapid disability accrual in patients with paediatric-onset MS., Methods: Using the global MSBase registry, we identified patients who were <18 years old at the onset of MS symptoms. The clinico-demographic characteristics examined as predictors of future MS Severity Score (MSSS) included sex, age at symptom onset, absence of disability at the initial assessment, maximum Expanded Disability Status Scale (EDSS) score, relapse frequency and presence of brainstem, pyramidal, visual or cerebellar symptoms in the first year. A Bayesian log-normal generalised linear mixed model adjusted for cumulative proportion of time on higher-efficacy disease-modifying therapies (DMTs) was used to analyse the data., Results: 672 patients (70% female) contributing 9357 visits were included. The median age at symptom onset was 16 (quartiles 15-17) years. Older age at symptom onset (exp(β)=1.10 (95% CI 1.04 to 1.17)), higher EDSS score (1.22 (1.12 to 1.34)) and pyramidal (1.31 (1.11 to 1.55)), visual (1.25 (1.10 to 1.44)) or cerebellar (1.18 (1.01 to 1.38)) symptoms in the first year were associated with higher MSSS. MSSS was reduced by 4% for every 24% increase in the proportion of time on higher-efficacy DMTs (0.96 (0.93 to 0.99))., Conclusions: A relatively later onset of MS in childhood, higher disability and pyramidal, visual or cerebellar symptoms during the first year predicted significant worsening in disability in patients with paediatric-onset MS. Persistent treatment with higher-efficacy DMTs was associated with a reduced rate of disability worsening., Competing Interests: Competing interests: SS has nothing to disclose. CM has nothing to disclose. IR served on scientific advisory boards, received conference travel support and/or speaker honoraria from Roche, Novartis, Merck and Biogen. ID has nothing to disclose. RA received honoraria as a speaker and for serving on scientific advisory boards from Bayer, Biogen, GSK, Merck, Novartis, Roche and Sanofi-Genzyme. SO has nothing to disclose. 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. DH received speaker honoraria and consulting fees from Biogen, Merck, Teva, Roche, Sanofi Genzyme and Novartis, as well as support for research activities from Biogen and Czech Ministry of Education (project Progres Q27/LF1). EKH received honoraria/research support from Biogen, Merck Serono, Novartis, Roche and Teva; has been a member of advisory boards for Actelion, Biogen, Celgene, MS, Novartis and SG; and has been supported by the Czech Ministry of Education research project PROGRES Q27/LF1. 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. MT received travel grants from Novartis, Bayer-Schering, Merck and Teva; and has participated in clinical trials by Sanofi Aventis, Roche and Novartis. CB received conference travel support from Biogen, Novartis, Bayer-Schering, Merck and Teva; and has participated in clinical trials by SA, Roche and Novartis. BY has nothing to disclose. SJK received personal compensation for participation in the Roche MaeStro Exchange Program and in Merck-Serono medical advisory board. MO has nothing to disclose. AL has received personal compensation for consulting, serving on a scientific advisory board, speaking or other activities from Biogen, Bristol Myers Squibb, Merck Serono, Mylan, Novartis, Roche, Sanofi/Genzyme and Teva. Her institutions have received research grants from Novartis (last 4 years). 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. AP has nothing to disclose. 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. 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. MJS has nothing to disclose. 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. YS has nothing to disclose. RG has nothing to disclose. AS has nothing to disclose. RT has nothing to disclose. MPA received honoraria as a 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. YF has nothing to disclose. 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, Novartis, Biogen, Sanofi-Genzyme, Teva, BioCSL and Merck; and received research or educational event support from Biogen, Novartis, Genzyme, Roche, Celgene and Merck., (© Author(s) (or their employer(s)) 2022. No commercial re-use. See rights and permissions. Published by BMJ.)

This protocol describes the estimation of the societal costs and quality-of-life (QOL) burden of multiple sclerosis (MS) in Lebanon. This cross-sectional, prevalence-based burden-of-illness study was carried out in a premier MS center in Lebanon. We enrolled Lebanese patients aged 18 years and older who had been diagnosed with MS more than 6 months. The study uses a bottom-up approach to estimate the cost-of-illness (COI) and QOL using a retrospective face-to-face interview questionnaire. This resource utilization questionnaire was adapted to the Lebanese context by clinical and health economics experts. The methodologies used to estimate the consumption of healthcare resources, informal care, and productivity losses are well-defined and aligned with the Lebanese healthcare system. Costs are presented overall and by MS severity levels. QOL is measured using the EuroQOL (EQ-5D-5 L) and Multiple Sclerosis International Quality of Life (MusiQoL) instrument. This protocol pioneers in informing the design of future COI and QOL studies in low - and middle-income countries (LMICs), as the methods used could be applied in similar LMICs. Furthermore, we provide recommendations and discuss the challenges of conducting a high-quality burden-of-illness study in LMICs and the steps taken to meet them, using the case of Lebanon.

Introduction: Gendered differences in career paths of medical graduates persist globally. We aim to explore the impact of domestic tethers on the career paths of physicians by studying gendered differences in domestic burdens of physicians as well as differences in perceptions around the impact of domestic work on professional advancement., Methods: A web-based survey including 38 questions was sent to all 3866 physician alumni of the top academic medical school in Lebanon. Data was collected between November 2018 and January 2019, with up to three invite reminders. Overall, 382 were included in the final analysis, 124 women (32%), 258 men (68%)., Results: The study had a response rate of 10.4%. Findings show that a greater percentage of men were married and had children (77.5% vs 62.1%, p = 0.004, 77.9% vs 51.6%, <0.001, respectively). Majority of both women and men held full-time positions (82.1% and 87.1%), having children however reduced the odds significantly [OR = 0.2, 95% CI: (0.1-0.6), p = 0.01]for women, while only older age reduced it for men (OR = 0.1,95% CI: (0.04-0.2), p<0.001]. Among full-time physicians, men and women spent similar time on professional activities (60.2hrs/wk vs 58.3hrs/wk, p = 0.32). Women spent more time on parenting and household work (23.5hrs/wk vs 10.4hrs/wk, <0.001; 8.9hrs/wk vs 6.0hrs/wk, p = 0.001, respectively). Women physicians' spouses contributed to 14.5 hours/week of total time on domestic activities whereas men physicians' spouses spent two folds more time on domestic activities (35.0 hours/week, P<0.001). Of physicians with children, a higher percentage of women than men reported that children prevented their career advancement or their participation in development opportunities (43.8% vs 15.9%, p<0.001; 50.0% vs 19.4%, p<0.001, respectively). A greater percentage of women than men scaled back their career after first child (31.3% vs 3.5%, <0.001). Of married/partnered physicians, fewer women than men reported their career took priority over their partner's when conflicts arose, (52.0% vs 86.0%, p<0.001)., Conclusion: These findings highlight the heavier impact of domestic tethers on the career paths of women physicians than men physicians. Men are more likely than women to hold full-time positions in the early advancement defining phases of their careers. Full-time women shoulder more domestic work than men and experience more professional advancement concessions. Closing persistent gender gaps in medicine requires addressing inequities in domestic burdens through strategies that include mentorship on domestic tethers, support of on-site child-care and advocacy for parental leave policies that encourage shared care-work., Competing Interests: The authors have declared that no competing interests exist.

The presence of a "central vein sign" (CVS) has been introduced as a biomarker for the diagnosis of multiple sclerosis (MS) and shown to have the ability to accurately differentiate MS from other white matter diseases (MS mimics). Following the development of susceptibility-based magnetic resonance venography that allowed the in vivo detection of CVS, a standard CVS definition was established by introducing the "40% rule" that assesses the number of MS lesions with CVS as a fraction of the total number of lesions to differentiate MS lesions from other types of lesions. The "50% rule," the "three-lesion criteria," and the "six-lesion criteria" were later introduced and defined. Each of these rules had high levels of sensitivity, specificity, and accuracy in differentiating MS from other diseases, which has been recognized by the Magnetic Resonance Imaging in MS (MAGNIMS) group and the Consortium of MS Centers task force. The North American Imaging in Multiple Sclerosis Cooperative even provided statements and recommendations aiming to refine, standardize and evaluate the CVS in MS. Herein, we review the existing literature on CVS and evaluate its added value in the diagnosis of MS and usefulness in differentiating it from other vasculopathies. We also review the histopathology of CVS and identify available automated CVS assessment methods as well as define the role of vascular comorbidities in the diagnosis of MS., (© 2021 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Objective: Multiple sclerosis (MS) is often associated with cognitive deficits. Accurate evaluation of the MS patients' cognitive performance is essential for diagnosis and treatment recommendation. The Brief International Cognitive Assessment in Multiple Sclerosis (BICAMS), widely used cognitive testing battery, examines processing speed, verbal and visuospatial learning, and memory. Our study aims to examine the psychometric properties of an Arabic version of the BICAMS and to provide normative values in a Lebanese sample., Method: The BICAMS, comprised of the Symbol Digit Modalities Test (SDMT), Brief Visuospatial Memory Test-Revised (BVMT-R), and a newly developed verbal learning/memory test, the Verbal Memory Arabic Test (VMAT), were administered on healthy subjects and MS patients. The sample consisted of 180 healthy individuals, of whom 63 were retested after 2-3 weeks. Forty-three MS patients matched with 43 healthy subjects based on age, sex, and years of education were assessed. A sample of 10 MS patients was also examined on two occasions. Test-retest reliability and criterion-related validity were examined, and regression-based norms were derived., Results: The test-retest correlations showed good evidence of reliability with coefficients ranging between 0.64 and 0.73 in the healthy sample, and between 0.43 and 0.92 in the MS sample. The BICAMS was able to discriminate between MS patients and matched healthy participants on the SDMT and BVMT-R. Normative data were comparable to other studies., Conclusions: This new Arabic version of the BICAMS shows initial good psychometric properties. While good evidence of VMAT's reliability was shown in the healthy participants, less test-retest reliability in this tool was seen in the MS group, and partial criterion-related validity was evident. This renders further examination of the VMAT. We provide regression-based norms for a Lebanese sample and encourage the use of this battery in both research and clinical settings.