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Comparative Effectiveness of Treatments for Relapse Prevention in Myelin Oligodendrocyte Glycoprotein Antibody-Associated Disease

In brief

Maintenance IVIG linked to 46% lower relapse risk in children with MOGAD

In a prospective study of 312 children with MOGAD, maintenance IVIG was associated with a 46% lower relapse risk in the analysis that accounted for treatment changes over time; 145 children relapsed during follow-up. The early-treatment analysis also favored IVIG, but results were not statistically significant, and residual confounding means trials are needed to confirm the benefit.

Journal
Neurology (Q1)
Published
7 October 2026
Study design
Randomized controlled trial
Evidence level
Level 1, High (CEBM 1b)
Authors
Akash Virupakshaiah, Vinicius Andreoli Schoeps, Jonathan Race, Claudia Gambrah-Lyles, Gina Chang, Michael Waltz, et al.
PMID
42842889
DOI
10.1212/WNL.0000000000218508

Why clinicians should know about it

  • Picked for Neurology (clinical) (paper of the day, 8 October 2026): IVIG reduces relapse risk in MOGAD

Abstract

BACKGROUND AND OBJECTIVES: The most effective treatment strategy to prevent relapses after a first myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) event remains unclear. Our objective was to evaluate the comparative effectiveness of maintenance therapies in preventing relapses in pediatric-onset MOGAD. METHODS: We analyzed prospectively collected data from November 2011 to August 2023 across 13 US pediatric neuroimmunology centers. Eligible patients had demyelinating disease onset before age 18 years, confirmed MOG-IgG positivity through cell-based assay, and negative aquaporin-4 IgG. Maintenance therapies were defined as ≥90 consecutive days of treatment and included IV immunoglobulin (IVIG), anti-CD20 therapy, oral corticosteroids, and other immunosuppressants. Two complementary approaches were used: (1) a primary full-course analysis using time-varying Cox proportional hazards models, adjusted for a priori-selected confounders, accounting for treatment changes throughout the disease course, and (2) a secondary early-course analysis using 1:1 propensity score-matched Cox models for the first qualifying treatment initiated within 90 days of onset, applying an intention-to-treat framework to minimize immortal time bias. RESULTS: Among 312 patients (58% female; mean age at onset 8.9 ± 4.2 years), 145 (46%) experienced at least 1 relapse during a median follow-up of 2.53 years (interquartile range 0.75-5.26). In the full-course analysis, IVIG was associated with a statistically significant 46% reduction in relapse risk (hazard ratio [HR] 0.54; 95% CI 0.31-0.93; p = 0.028). Anti-CD20 therapy (HR 0.98; 95% CI 0.56-1.72), oral corticosteroids (HR 0.86; 95% CI 0.55-1.35), and other immunosuppressants showed no significant association with relapse risk. In the early-course propensity-matched analysis, directional trends favoring IVIG (n = 23 matched pairs; HR 0.29; 95% CI 0.07-1.14; p = 0.076) and anti-CD20 therapy (n = 6 matched pairs; HR 0.34; 95% CI 0.03-3.82; p = 0.38) were observed but did not reach statistical significance, likely due to limited sample sizes. Oral corticosteroids showed a nonsignificant trend toward increased relapse risk in early-course analysis (HR 2.18; 95% CI 0.79-6.31; p = 0.13). Older age at disease onset independently increased relapse hazard (HR 1.67 per year; 95% CI 1.49-1.87; p < 0.001), and prior relapse count was a strong predictor of future relapse risk. DISCUSSION: In this large, prospective, multicenter pediatric MOGAD cohort, IVIG was the only treatment consistently associated with reduced relapse risk across both analytical approaches, supporting its potential role as first-line maintenance therapy. Anti-CD20 therapy showed directional trends warranting further investigation. Key limitations include potential residual confounding by indication and small sample sizes in certain treatment categories. Randomized controlled trials are needed to confirm these findings.

Abstract as published, via PubMed.

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For healthcare professionals. The summary is generated by AI from the published abstract, and the evidence level is assigned automatically from the study design on the Oxford CEBM hierarchy. Neither is medical advice. Read the full paper before changing practice.