Neil Basu1, Gareth T Jones, Gary J Macfarlane, Katie L Druce. 1. From the Epidemiology Group (Basu, Jones, Macfarlane), School of Medicine, Medical Sciences and Nutrition, and Aberdeen Centre for Arthritis and Musculoskeletal Health (Basu, Jones, Macfarlane), University of Aberdeen; and Arthritis Research UK Centre for Epidemiology (Druce), Centre for Musculoskeletal Research, Manchester Academic Health Science Centre, The University of Manchester, United Kingdom.
Abstract
OBJECTIVE: The considerable heterogeneity of rheumatoid arthritis (RA)-related fatigue is the greatest challenge to determining pathogenesis. The identification of homogenous subtypes of severe fatigue would inform the design and analysis of experiments seeking to characterize the likely numerous causal pathways that underpin the symptom. This study aimed to identify and validate such fatigue subtypes 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 antirheumatic drugs (DMARD cohort, n = 522) or commencing anti-tumor necrosis factor therapy (anti-TNF cohort, n = 3909). In those reporting severe fatigue (Short-Form 36 vitality ≤ 12.5), this cross-sectional analysis applied hierarchical clustering with weighted-average linkage identified clusters of pain, fatigue, mental health (all Short-Form 36), disability (Health Assessment Questionnaire), and inflammation (erythrocyte sedimentation rate) in the DMARD cohort. K-means clustering sought to validate the solution in the anti-TNF cohort. Clusters were characterized using a priori generated symptom definitions and between-cluster comparisons. RESULTS: Four severe fatigue clusters, labeled 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, although 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.
OBJECTIVE: The considerable heterogeneity of rheumatoid arthritis (RA)-related fatigue is the greatest challenge to determining pathogenesis. The identification of homogenous subtypes of severe fatigue would inform the design and analysis of experiments seeking to characterize the likely numerous causal pathways that underpin the symptom. This study aimed to identify and validate such fatigue subtypes 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 antirheumatic drugs (DMARD cohort, n = 522) or commencing anti-tumornecrosis factor therapy (anti-TNF cohort, n = 3909). In those reporting severe fatigue (Short-Form 36 vitality ≤ 12.5), this cross-sectional analysis applied hierarchical clustering with weighted-average linkage identified clusters of pain, fatigue, mental health (all Short-Form 36), disability (Health Assessment Questionnaire), and inflammation (erythrocyte sedimentation rate) in the DMARD cohort. K-means clustering sought to validate the solution in the anti-TNF cohort. Clusters were characterized using a priori generated symptom definitions and between-cluster comparisons. RESULTS: Four severe fatigue clusters, labeled 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, although the proportion of participants in each cluster differed (basic = 28.7%; affective = 30.2%; global = 24.1%; inflammatory = 16.9%). CONCLUSIONS: Among RApatients 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.
Authors: Alexandra Braun; Dimitar Evdokimov; Johanna Frank; Paul Pauli; Nurcan Üçeyler; Claudia Sommer Journal: PLoS One Date: 2020-12-28 Impact factor: 3.240
Authors: Kristien Van der Elst; Patrick Verschueren; Diederik De Cock; An De Groef; Veerle Stouten; Sofia Pazmino; Johanna Vriezekolk; Johan Joly; Philip Moons; René Westhovens Journal: RMD Open Date: 2020-04