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

ABSTRACT:

Background

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.

Methods

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

SUBMITTER: Guo J 

PROVIDER: S-EPMC12923449 | biostudies-literature | 2026 Feb

REPOSITORIES: biostudies-literature