Multiple sclerosis subgroups: Data-driven clusters based on patient-reported outcomes and a large clinical sample.

ABSTRACT:

Background

While standard clinical assessments provide great value for people with multiple sclerosis (PwMS), they are limited in their ability to characterize patient perspectives and individual-level symptom heterogeneity.

Objectives

To identify PwMS subgroups based on patient-reported outcomes (PROs) of physical, cognitive, and emotional symptoms. We also sought to connect PRO-based subgroups with demographic variables, functional impairment, hypertension and smoking status, traditional qualitative multiple sclerosis (MS) symptom groupings, and neuroperformance measurements.

Methods

Using a cross-sectional design, we applied latent profile analysis (LPA) to a large database of PROs; analytic sample N = 6619).

Results

We identified nine distinct MS sub

SUBMITTER: De Nadai AS 

PROVIDER: S-EPMC11568927 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature