Background: We sought to identify an optimal oral corticosteroid regimen at the onset of myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD), which would delay time to first relapse while minimising cumulative corticosteroid exposure.Methods: In a retrospective multicentre cohort study, Cox proportional hazards models examined the relationship between corticosteroid course as a time-varying covariate and time to first relapse. Simon-Makuch and Kaplan-Meier plots identified an optimal dosing strategy.Results: We evaluated 109 patients (62 female, 57%; 41 paediatric, 38%; median age at onset 26 years, (IQR 8–38); median follow-up 6.2 years (IQR 2.6–9.6)). 76/109 (70%) experienced a relapse (median time to first relapse 13.7 months; 95% CI 8.2 to 37.9). In a multivariable model, higher doses of oral prednisone delayed time to first relapse with an effect estimate of 3.7% (95% CI 0.8% to 6.6%; p=0.014) reduced hazard of relapse for every 1 mg/day dose increment. There was evidence of reduced hazard of relapse for patients dosed ≥12.5 mg/day (HR 0.21, 95% CI 0.07 to 0.6; p=0.0036), corresponding to a 79% reduction in relapse risk. There was evidence of reduced hazard of relapse for those dosed ≥12.5 mg/day for at least 3 months (HR 0.12, 95% CI 0.03 to 0.44; p=0.0012), corresponding to an 88% reduction in relapse risk compared with those never treated in this range. No patient with this recommended dosing at onset experienced a Common Terminology Criteria for Adverse Events grade >3 adverse effect.Conclusions: The optimal dose of 12.5 mg of prednisone daily in adults (0.16 mg/kg/day for children) for a minimum of 3 months at the onset of MOGAD delays time to first relapse.

Background: Effectiveness of cladribine tablets, an oral disease-modifying treatment (DMT) for multiple sclerosis (MS), was established in clinical trials and confirmed with real-world experience. Objectives: Use real-world data to compare treatment patterns and clinical outcomes in people with MS (pwMS) treated with cladribine tablets versus other oral DMTs. Methods: Retrospective treatment comparisons were based on data from the international MSBase registry. Eligible pwMS started treatment with cladribine, fingolimod, dimethyl fumarate, or teriflunomide tablets from 2018 to mid-2021 and were censored at treatment discontinuation/switch, death, loss to follow-up, pregnancy, or study period end. Treatment persistence was evaluated as time to discontinuation/switch; relapse outcomes included time to first relapse and annualized relapse rate (ARR). Results: Cohorts included 633 pwMS receiving cladribine tablets, 1195 receiving fingolimod, 912 receiving dimethyl fumarate, and 735 receiving teriflunomide. Individuals treated with fingolimod, dimethyl fumarate, or teriflunomide switched treatment significantly more quickly than matched cladribine tablet cohorts (adjusted hazard ratio (95% confidence interval): 4.00 (2.54–6.32), 7.04 (4.16–11.93), and 6.52 (3.79–11.22), respectively). Cladribine tablet cohorts had significantly longer time-to-treatment discontinuation, time to first relapse, and lower ARR, compared with other oral DMT cohorts. Conclusion: Cladribine tablets were associated with a significantly greater real-world treatment persistence and more favorable relapse outcomes than all oral DMT comparators.

Background and Objectives In multiple sclerosis (MS), accelerated aging of the immune system (immunosenescence) may be associated with disease onset or drive progression. DNA methylation (DNAm) is an epigenetic factor that varies among lymphocyte subtypes, and cell-specific DNAm is associated with MS. DNAm varies across the life span and can be used to accurately estimate biological age acceleration, which has been linked to a range of morbidities. The objective of this study was to test for cell-specific epigenetic age acceleration (EAA) in people with MS. Methods This was a case-control study of EAA using existing DNAm data from several independent previously published studies. Data were included if .idat files from Illumina 450K or EPIC arrays were available for both a case with MS and an age-matched and sex-matched control, from the same study. Multifactor statistical modeling was performed to assess the primary outcome of EAA. We explored the relationship of EAA and MS, including interaction terms to identify immune cell-specific effects. Cell-sorted DNA methylation data from 3 independent datasets were used to validate findings. Results We used whole blood DNA methylation data from 583 cases with MS and 643 non-MS controls to calculate EAA using the GrimAge algorithm. The MS group exhibited an increased EAA compared with controls (approximately 9 mths, 95% CI 3.6–14.4), p = 0.001). Statistical deconvolution showed that EAA is associated with MS in a B cell–dependent manner (β_int = 1.7, 95% CI 0.3–2.8), p = 0.002), irrespective of B-cell proportions. Validation analysis using 3 independent datasets enriched for B cells showed an EAA increase of 5.1 years in cases with MS compared with that in controls (95% CI 2.8–7.4, p = 5.5 × 10⁻⁵). By comparison, there was no EAA difference in MS in a T cell–enriched dataset. We found that EAA was attributed to the DNAm surrogates for Beta-2-microglobulin (difference = 47,546, 95% CI 10,067–85,026; p = 7.2 × 10⁻⁵), and smoking pack-years (difference = 8.1, 95% CI 1.9–14.2, p = 0.002). Discussion This study provides compelling evidence that B cells exhibit marked EAA in MS and supports the hypothesis that premature B-cell immune senescence plays a role in MS. Future MS studies should focus on age-related molecular mechanisms in B cells.

Objective: To compare the clinical effectiveness of high- and low-efficacy treatments in patients with recently active and inactive secondary progressive multiple sclerosis (SPMS) after accounting for therapeutic lag. Methods: Patients treated with high- (natalizumab, alemtuzumab, mitoxantrone, ocrelizumab, rituximab, cladribine, fingolimod) or low-efficacy (interferon β, glatiramer acetate, teriflunomide) therapies after SPMS onset were selected from MSBase and OFSEP, two large observational cohorts. Therapeutic lag was estimated for each patient based on their demographic and clinical characteristics. Propensity score was used to match patients treated with high and low-efficacy therapies. Outcomes after disregarding the period of therapeutic lag were compared in paired, pairwise-censored analyses. Results: 1000 patients were included in the primary analysis. Patients with active SPMS treated with high-efficacy therapy experienced less frequent relapses than those on low-efficacy therapy (hazard ratio [HR] 0.7, p=0.006). In patients with inactive SPMS, there was no evidence for a difference in relapse frequency between groups (HR=0.8,p=0.39). No evidence for a difference in the risk of disability progression was observed. Conclusion: In treated patients with SPMS, high-efficacy therapy is superior to low-efficacy therapy in reducing relapses in patients with active, but not those with inactive, SPMS. However, more potent therapies do not offer an advantage in reducing disability progression in this patient group. Classification of Evidence: This study provides class III evidence that high-efficacy therapy is superior to low-efficacy therapy in reducing relapses in patients with active SPMS whilst we did not find a difference in disability progression between patients treated with high- and low-efficacy therapy.

In aquaporin-4 antibody-positive neuromyelitis optica spectrum disorder (AQP4-IgG NMOSD), disability accrual is mostly attributed to relapses. This study aimed to assess the prevalence of progression independent of relapse activity (PIRA) and relapse-associated worsening (RAW) in AQP4-IgG NMOSD. This was a retrospective cohort study of patients with AQP4-IgG NMOSD enrolled in the MSBase international data registry. Patients required a minimum of 3 recorded Expanded Disability Status Scale (EDSS) scores: baseline, event, and a 6-month confirmation score. Presence and absence of relapses between the baseline and event EDSS scores determined RAW and PIRA, respectively. Descriptive statistics were used to present the results. A total of 181 patients followed for a median of 4.5 years (Q1 1.7, Q3 7.8) were included. Most patients were female (88.4%), and the median age at disease onset was 38.1 years. Overall, 4 patients (2.2%) developed 5 incidences of PIRA and 13 patients developed RAW (7.2%). This multicenter study highlights that PIRA is very rare in AQP4-IgG NMOSD. Limitations of this study include the sole focus of overall EDSS to measure disability, lack of requirement for a second EDSS score to confirm baseline EDSS, and the absence of magnetic resonance imaging information for all patients.

Background: Disability progression is a key milestone in the disease evolution of people with multiple sclerosis (PwMS). Prediction models of the probability of disability progression have not yet reached the level of trust needed to be adopted in the clinic. A common benchmark to assess model development in multiple sclerosis is also currently lacking. Methods: Data of adult PwMS with a follow-up of at least three years from 146 MS centers, spread over 40 countries and collected by the MSBase consortium was used. With basic inclusion criteria for quality requirements, it represents a total of 15, 240 PwMS. External validation was performed and repeated five times to assess the significance of the results. Transparent Reporting for Individual Prognosis Or Diagnosis (TRIPOD) guidelines were followed. Confirmed disability progression after two years was predicted, with a confirmation window of six months. Only routinely collected variables were used such as the expanded disability status scale, treatment, relapse information, and MS course. To learn the probability of disability progression, state-of-the-art machine learning models were investigated. The discrimination performance of the models is evaluated with the area under the receiver operator curve (ROC-AUC) and under the precision recall curve (AUC-PR), and their calibration via the Brier score and the expected calibration error. All our preprocessing and model code are available at https://gitlab.com/edebrouwer/ms_benchmark, making this task an ideal benchmark for predicting disability progression in MS. Findings: Machine learning models achieved a ROC-AUC of 0⋅71 ± 0⋅01, an AUC-PR of 0⋅26 ± 0⋅02, a Brier score of 0⋅1 ± 0⋅01 and an expected calibration error of 0⋅07 ± 0⋅04. The history of disability progression was identified as being more predictive for future disability progression than the treatment or relapses history. Conclusions: Good discrimination and calibration performance on an external validation set is achieved, using only routinely collected variables. This suggests machine-learning models can reliably inform clinicians about the future occurrence of progression and are mature for a clinical impact study.