Subgrouping a large U.S. sample of patients with fibromyalgia using the fibromyalgia impact questionnaire-revised
Pérez-Aranda, Adrián (Universitat Autònoma de Barcelona. Departament de Psicologia Bàsica, Evolutiva i de l'Educació)
Jones, Kim (Linfield University and School of Medicine. School of Nursing)
López-del-Hoyo, Yolanda (Universidad de Zaragoza. Departamento de Psicología y Sociología)
Oliván-Arévalo, Rebeca (Parc Sanitari Sant Joan de Déu. Unitat de Docència, Recerca i Innovació)
Kratz, Anna (University of Michigan. Department of Physical Medicine and Rehabilitation)
Williams, David J. (University of Michigan. Departments of Anesthesiology, Internal Medicine, Psychiatry, and Psychology)
Luciano, Juan V. (Parc Sanitari Sant Joan de Déu. Unitat de Docència, Recerca i Innovació)
Feliu-Soler, Albert (Universitat Autònoma de Barcelona. Departament de Psicologia Bàsica, Evolutiva i de l'Educació)
Mist, Scott (Oregon Health & Science University. Department of Anesthesiology & Perioperative Medicine)

Data:	2021
Resum:	Fibromyalgia (FM) is a heterogeneous and complex syndrome; different studies have tried to describe subgroups of FM patients, and a 4-cluster classification based on the Fibromyalgia Impact Questionnaire-Revised (FIQR) has been recently validated. This study aims to cross-validate this classification in a large US sample of FM patients. A pooled sample of 6280 patients was used. First, we computed a hierarchical cluster analysis (HCA) using FIQR scores at item level. Then, a latent profile analysis (LPA) served to confirm the accuracy of the taxonomy. Additionally, a cluster calculator was developed to estimate the predicted subgroup using an ordinal regression analysis. Self-reported clinical measures were used to examine the external validity of the subgroups in part of the sample. The HCA yielded a 4-subgroup distribution, which was confirmed by the LPA. Each cluster represented a different level of severity: "Mild-moderate", 'moderate', 'moderate-severe', and 'severe'. Significant differences between clusters were observed in most of the clinical measures (e. g. , fatigue, sleep problems, anxiety). Interestingly, lower levels of education were associated with higher FM severity. This study corroborates a 4-cluster distribution based on FIQR scores to classify US adults with FM. The classification may have relevant clinical implications for diagnosis and treatment response.
Drets:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.
Llengua:	Anglès
Document:	Article ; recerca ; Versió publicada
Matèria:	Fibromyalgia Impact Questionnaire Revised ; Fibromyalgia ; Clusters ; Latent profile analysis ; Hierarchical cluster
Publicat a:	International journal of environmental research and public health, Vol. 18, núm. 1 (2021) , p. 247, ISSN 1660-4601

Adreça alternativa: https://www.mdpi.com/1660-4601/18/1/247
DOI: 10.3390/ijerph18010247
PMID: 33396279

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