Protocol - modelling predictors for relapsing disease in MOGAD

Abstract

In myelin oligodendrocyte glycoprotein antibody associated disease (MOGAD), only approximately 40%-60% of patients develop a relapsing disease course, for which the preventative treatment is long-term immunotherapy. Due to its significant adverse effect burden, long-term immunosuppression should generally be reserved only for patients likely to relapse, but there are currently no widely accepted predictors of developing relapsing MOGAD. A recent literature search published in February 2023 found no predictors of relapse in paediatric MOGAD.

Identifying the predictive value of the combined risk factors for developing relapsing disease is of direct interest for the patient and for the treating neurologist, who needs to make the decision to commence maintenance therapy in MOGAD. Equally, quantifying the degree of uncertainty of prediction is important in the transparent communication with the patient, who needs to make an informed decision regarding the treatment. Studies in literature have most often studied predictors of relapse individually, but not combined. Having completed a scoping review of the available literature on predictors of relapsing MOGAD, our planned data analysis will aim to test the value of a model including the relevant predictors of developing relapsing MOGAD in adult patients with MOGAD (with onset in adulthood or childhood), using an observational data set (clinical data of adult patients with MOGAD – NMOSD&MOGAD Clinic, Nottingham Centre for MS and Neuroinflammation) and test the resulting model in an independent dataset sample (clinical data of adult MOGAD patients, the NMOSD Excellence Service, Walton Centre Liverpool).