Disease burden in inflammatory arthritis: an unsupervised machine learning approach of the COVAD-2 e-survey dataset.

ABSTRACT:

Objectives

To comprehensively compare the disease burden among patients with RA, PsA and AS using Patient-Reported Outcome Measurement Information System (PROMIS) scores and to identify distinct patient clusters based on comorbidity profiles and PROMIS outcomes.

Methods

Data from the global COVID-19 Vaccination in Autoimmune Diseases (COVAD) 2 e-survey were analysed. Patients with RA, PsA or AS undergoing treatment with DMARDs were included. PROMIS scores (global physical health, global mental health, fatigue 4a and physical function short form 10a), comorbidities and other variables were compared among the three groups, stratified by disease activity status. Unsupervised hierarchical clustering with eXtreme Gradient Boosting feature importance analysis was performed to iden

SUBMITTER: Venerito V 

PROVIDER: S-EPMC12007600 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature