Subgrouping a Large U.S. Sample of Patients with Fibromyalgia Using the Fibromyalgia Impact Questionnaire-Revised.

Int J Environ Res Public Health

AGORA Research Group, Teaching, Research & Innovation Unit, Parc Sanitari Sant Joan de Déu, 08830 St. Boi de Llobregat, Spain.

Published: December 2020

AI Article Synopsis

  • Fibromyalgia (FM) is a complex syndrome, and a recent study validated a 4-cluster classification system based on the Fibromyalgia Impact Questionnaire-Revised (FIQR) in a large sample of 6,280 US patients.
  • Hierarchical cluster analysis (HCA) and latent profile analysis (LPA) confirmed four severity levels: "Mild-moderate," "moderate," "moderate-severe," and "severe," with significant differences in clinical measures like fatigue and anxiety among the clusters.
  • The research suggests that lower education levels correlate with higher FM severity, and the findings could impact diagnosis and treatment strategies for FM patients.

Article Abstract

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.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7796452PMC
http://dx.doi.org/10.3390/ijerph18010247DOI Listing

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