A mixture model for differentiating longitudinal courses of multiple sclerosis

Abstract

BackgroundMultiple sclerosis has a broad spectrum of clinical courses. Early identification of patients at greater risk of accumulating disability is essential. ObjectivesIdentify groups of patients with similar presentation through a mixture model and predict their trajectories over the years. MethodsRetrospective study of patients from 1994 to 2019. We performed a latent profile analysis followed by a latent transition analysis based on eight parameters: age, disease duration, EDSS, number of relapses, multi-topographic symptoms, motor impairment, sphincter impairment, and infratentorial lesions. ResultsWe included 629 patients, regardless of the phenotypical classification. We identified three distinct groups at the beginning and end of the follow-up. The three-classes model disclosed the “No disability regardless disease duration” (NDRDD) class with low EDSS and younger patients, the “Disability within a short disease duration” (DSDD) class with the worse disability besides short illness, and the “Disability within a long disease duration” (DLDD) class that achieved high EDSS over a long disease duration. EDSS, disease duration, and no sphincter impairment had the best entropy to distinguish classes at the initial presentation. Over time, the patients from NDRDD had a 52.1 % probability of changing to DLDD and 7.7 % of changing to DSDD. ConclusionsWe identified three groups of clinical presentations and their evolution over time based on considered prognostic factors. The most likely transition is from NDRDD to DLDD.