Disability progression in multiple sclerosis: a latent class analysis of predictors
Jie Guo, Tomas Olsson, Lars Alfredsson, Anna Karin Hedström

TL;DR
This study identifies different patterns of disability progression in multiple sclerosis and finds that early clinical and lifestyle factors predict long-term outcomes.
Contribution
The novel use of latent class trajectory modeling reveals seven distinct disability progression patterns in MS patients.
Findings
Seven distinct EDSS trajectories were identified, with group 4 showing stable low disability and groups 5–7 showing increasing disability.
Older age, higher baseline EDSS, frequent relapses, and lifestyle factors like obesity and smoking were linked to worse outcomes.
High physical activity was associated with lower odds of unfavorable disability progression.
Abstract
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…
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Taxonomy
TopicsMultiple Sclerosis Research Studies · Systemic Lupus Erythematosus Research · Viral Infections and Immunology Research
