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.
Psychosom Med. 2017 Nov/Dec;79(9):1051-1058. doi: 10.1097/PSY.0000000000000498.
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.
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.
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%).
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.
类风湿关节炎（RA）相关疲劳的显著异质性是确定发病机制的最大挑战。确定严重疲劳的同质亚类将为设计和分析旨在描述可能为数众多的潜在因果途径的实验提供信息，这些途径是支撑该症状的基础。本研究旨在确定并验证 RA 患者中存在的此类疲劳亚类。
从英国风湿病学会生物制剂登记处招募的接受传统疾病修饰抗风湿药物（DMARD 队列，n = 522）或开始抗肿瘤坏死因子治疗（抗 TNF 队列，n = 3909）的 RA 患者中获取数据。在报告严重疲劳（SF-36 活力≤12.5）的患者中，该横断面分析采用层次聚类和加权平均链接，确定 DMARD 队列中疼痛、疲劳、心理健康（所有 SF-36）、残疾（健康评估问卷）和炎症（红细胞沉降率）的聚类。K-均值聚类试图在抗 TNF 队列中验证该解决方案。使用预先确定的症状定义和聚类间比较来描述聚类。
在 DMARD 队列中确定了 4 种严重疲劳聚类，分别为基础型（46%）、情感型（40%）、炎症型（4.5%）和整体型（8.9%）。所有聚类均具有严重的疼痛和残疾程度，并通过心理健康状况差和炎症程度高来区分。在抗 TNF 队列中也存在相同的症状聚类，尽管每个聚类的参与者比例不同（基础型=28.7%；情感型=30.2%；整体型=24.1%；炎症型=16.9%）。
在两个不同的 RA 队列中招募的 RA 伴严重疲劳患者中，确定并验证了具有临床意义的聚类。这些聚类可能为未来的机制研究提供基础，并最终支持疲劳管理的分层方法。
