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

Research output: Contribution to journalArticle

3 Citations (Scopus)
13 Downloads (Pure)

Abstract

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.
Original languageEnglish
Pages (from-to)1051-1058
Number of pages8
JournalPsychosomatic Medicine
Volume79
Issue number9
Early online date31 May 2017
DOIs
Publication statusPublished - Nov 2017

Fingerprint

Fatigue
Rheumatoid Arthritis
Antirheumatic Agents
ametantrone
Cluster Analysis
Mental Health
Inflammation
Pain
Biological Products
Cross-Sectional Studies

Keywords

  • fatigue
  • pain
  • disability
  • cluster
  • rheumatoid arthritis

Cite this

@article{93dbfed36bc74bd885f7d5bf7f5ab557,
title = "Identification and Validation of Clinically Relevant Clusters of Severe Fatigue in Rheumatoid Arthritis",
abstract = "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.",
keywords = "fatigue, pain, disability, cluster, rheumatoid arthritis",
author = "Neil Basu and Jones, {Gareth T} and MacFarlane, {Gary J} and Druce, {Katie L}",
note = "The authors have no conflicts of interest to disclose. This work was supported by the Institute of Applied Health Sciences, University of Aberdeen, who provided KD’s PhD studentship. The BSR commissioned the BSRBR-RA as a UK-wide national project to investigate the safety of biologic agents in routine medical practice. BSR receives restricted income from UK pharmaceutical companies, presently Abbott Laboratories, Merck, Pfizer, Roche, UCB and SOBI. This income finances a wholly separate contract between the BSR and the University of Manchester who provide and oversee the BSRBR-RA data collection, management and analysis service. The principal investigators and their team have full academic freedom and are able to work independently of pharmaceutical industry influence. All decisions concerning analyses, interpretation and publication are made autonomously of any industrial contribution.",
year = "2017",
month = "11",
doi = "10.1097/PSY.0000000000000498",
language = "English",
volume = "79",
pages = "1051--1058",
journal = "Psychosomatic Medicine",
issn = "0033-3174",
publisher = "Lippincott Williams & Wilkins",
number = "9",

}

TY - JOUR

T1 - Identification and Validation of Clinically Relevant Clusters of Severe Fatigue in Rheumatoid Arthritis

AU - Basu, Neil

AU - Jones, Gareth T

AU - MacFarlane, Gary J

AU - Druce, Katie L

N1 - The authors have no conflicts of interest to disclose. This work was supported by the Institute of Applied Health Sciences, University of Aberdeen, who provided KD’s PhD studentship. The BSR commissioned the BSRBR-RA as a UK-wide national project to investigate the safety of biologic agents in routine medical practice. BSR receives restricted income from UK pharmaceutical companies, presently Abbott Laboratories, Merck, Pfizer, Roche, UCB and SOBI. This income finances a wholly separate contract between the BSR and the University of Manchester who provide and oversee the BSRBR-RA data collection, management and analysis service. The principal investigators and their team have full academic freedom and are able to work independently of pharmaceutical industry influence. All decisions concerning analyses, interpretation and publication are made autonomously of any industrial contribution.

PY - 2017/11

Y1 - 2017/11

N2 - 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.

AB - 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.

KW - fatigue

KW - pain

KW - disability

KW - cluster

KW - rheumatoid arthritis

U2 - 10.1097/PSY.0000000000000498

DO - 10.1097/PSY.0000000000000498

M3 - Article

C2 - 28570437

VL - 79

SP - 1051

EP - 1058

JO - Psychosomatic Medicine

JF - Psychosomatic Medicine

SN - 0033-3174

IS - 9

ER -