ArticleInternational journal of environmental research and public health2020
Subgrouping a Large U.S. Sample of Patients with Fibromyalgia Using the Fibromyalgia Impact Questionnaire-Revised.
Article in International journal of environmental research and public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.
- Cluster analysis in fibromyalgia: a systematic review.Rheumatology international · 2024Pooled it
- Two Neuroanatomical Subtypes in Fibromyalgia Patients: Distinct Morphological Patterns and Treatment Outcomes.CNS neuroscience & therapeutics · 2025Trial
- Sociodemographic Factors, but Not Rurality, Explain Limited Variance in Fibromyalgia Severity: A Secondary Analysis of Two Randomized Clinical Trials.Pain medicine (Malden, Mass.) · 2026Article
- Psychiatric comorbidity patterns across disability-based fibromyalgia phenotypes.CNS spectrums · 2026Article
- REAC Neurobiological Modulation as a Precision Medicine Treatment for Fibromyalgia.Journal of personalized medicine · 2023Article
- Does Pain Acceptance Contribute to Improved Functionality through Walking in Women with Fibromyalgia? Looking at Depressive Comorbidity.International journal of environmental research and public health · 2023Article
Corrections and comments
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Authors and funding
9 authors at 6 institutions in 2 countries.
Funding
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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Registered trials
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