Differences in symptom experience among patients with systemic sclerosis: a cluster analytic approach to identifying subgroups.

ABSTRACT:

Objectives

Symptoms of people who have SSc are heterogeneous and difficult to address clinically. Because diverse symptoms often co-occur and may share common underlying mechanisms, identifying symptoms that cluster together may better target treatment approaches. We sought to identify and characterize patient subgroups based on symptom experience.

Methods

An exploratory hierarchical agglomerative cluster analysis was conducted to identify subgroups from a large SSc cohort from a single US academic medical centre. Patient-reported symptoms of pain interference, fatigue, sleep disturbance, dyspnoea, depression and anxiety were used for clustering. A multivariate analysis of variance (MANOVA) was used to examine the relative contribution of each variable across subgroups. Anal

SUBMITTER: Murphy SL 

PROVIDER: S-EPMC9910572 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature