External validation of the MOG-AR score for predicting post-attack relapse risk in a chinese cohort with MOGAD

Myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) frequently follows a relapsing course, necessitating early identification of patients at high risk of relapse to guide management strategies. Until recently, no validated risk assessment tool was available. The MOGAD Relapse (MOG-AR) score, developed within a Chinese cohort, stratifies post-attack relapse risk using various clinical factors. Our study aimed to externally validate the MOG-AR score in an independent Chinese MOGAD cohort.

We conducted a retrospective analysis of 157 MOGAD patients from a tertiary center in South China, spanning June 2015 to May 2023. Clinical data were collected, and each patient's MOG-AR score was calculated based on five predictors: onset age, sex, attack phenotype, immunosuppressive therapy, and oral corticosteroid duration. Model performance was evaluated using Harrell's C-index for discrimination, calibration plots for calibration, and Kaplan-Meier analysis for comparing risk between MOG-AR score groups.

The cohort's median onset age was 27 years, with 51.6 % female and 78.3 % adults. Optic neuritis was the most common initial presentation (40.8 %), followed by transverse myelitis (14.0 %). During a median disease duration of 46 months, 87 patients (55.4 %) experienced at least one relapse. The MOG-AR score demonstrated a C-index of 0.72 (95 % confidence interval 0.63-0.81) and showed favorable alignment with calibration curves. Kaplan-Meier survival curves stratified by MOG-AR grade exhibited clear separation (log-rank p < 0.001).

The MOG-AR score was successfully externally validated in our MOGAD cohort, demonstrating strong discrimination and calibration in predicting post-attack relapses. Patients with higher MOG-AR scores exhibited significantly elevated relapse risks and shorter time to relapse.