Disability progression in multiple sclerosis: a latent class analysis of predictors

Multiple sclerosis (MS) is a heterogeneous disease with highly variable long-term outcomes. We aimed to identify patterns of disability progression and their determinants to improve individualized risk assessment and support clinical decision-making.

We applied latent class trajectory modeling to Expanded Disability Status Scale (EDSS) data from 3163 newly diagnosed relapsing-onset MS cases in the Swedish Epidemiological Investigation of MS (2005-2019). Baseline demographics, clinical, and lifestyle data were collected at diagnosis, and participants were followed through the Swedish MS registry. Multivariate logistic regression was used to examine associations between baseline characteristics and trajectory group membership. Kaplan-Meier analysis estimated time to confirmed disability worsening, EDSS 3 and EDSS 4 across trajectory groups.

Seven distinct EDSS trajectories were identified. Group 4 (n = 1149) was the most common and characterized by stable, low disability. Groups 5-7 showed steadily increasing disability and were categorized as unfavorable (n = 662). In multivariate models, older age at diagnosis, longer baseline disease duration, higher baseline EDSS score, more frequent early relapses, poor cognitive performance, and autoimmune comorbidities were associated with unfavorable progression. Among lifestyle factors, obesity, smoking, and low sun exposure were linked to worse outcomes, while high physical activity decreased the odds of unfavorable progression. No significant association was observed for baseline vitamin D levels. Time to confirmed disability progression outcomes differed substantially across trajectory groups.

Early clinical and lifestyle factors were associated with long-term outcomes. These findings illustrate the heterogeneity of MS progression and support further investigation of early modifiable factors influencing long-term outcomes.