Identification and Validation of Clinically Relevant Clusters of Severe Fatigue in Rheumatoid Arthritis

Objectives: The considerable heterogeneity of rheumatoid arthritis (RA) related fatigue is the greatest challenge to determining pathogenesis. The identification of homogenous sub-types of severe fatigue would inform the design and analysis of experiments seeking to characterise the likely numerous causal pathways which underpin the symptom. This study aimed to identify and validate such fatigue sub-types in patients with RA.
Methods: Data were obtained from patients recruited to the British Society for Rheumatology Biologics register for RA, as either receiving traditional Disease Modifying Anti-Rheumatic Drugs (DMARD cohort, n=522) or commencing anti-TNF therapy (anti-TNF cohort, n=3909). In those reporting severe fatigue (SF36 vitality≤12.5), this cross-sectional analysis applied hierarchical clustering with weighted-average linkage identified clusters of pain, fatigue, mental health (all SF36), disability (HAQ) and inflammation (ESR) in the DMARD cohort. K-means clustering sought to validate the solution in the anti-TNF cohort. Clusters were characterised using a priori generated symptom definitions and between-cluster comparisons.
Results: Four severe fatigue clusters, labelled as basic (46%), affective (40%), inflammatory (4.5%) and global (8.9%) were identified in the DMARD cohort. All clusters had severe levels of pain and disability, and were distinguished by the presence/absence of poor mental health and high inflammation. The same symptom clusters were present in the anti-TNF cohort, though the proportion of participants in each cluster differed (basic:28.7%, affective:30.2%, global:24.1%, inflammatory:16.9%).
Conclusions: Among RA patients with severe fatigue, recruited to two diverse RA cohorts, clinically relevant clusters were identified and validated. These may provide the basis for future mechanistic studies and ultimately support a stratified approach to fatigue management.