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Cluster analysis in fibromyalgia: a systematic review.

Anna Carolyna Gianlorenço1,2, Valton Costa1,2, Walter Fabris-Moraes2

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|May 15, 2024
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Fibromyalgia syndrome (FMS) patient subgroups exist, identified through cluster analysis. These diverse profiles highlight the need for tailored treatments and better healthcare resource allocation for FMS management.

Keywords:
Cluster analysisFibromyalgiaSystematic review

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Area of Science:

  • Rheumatology
  • Medical Informatics
  • Psychiatry

Background:

  • Fibromyalgia syndrome (FMS) presents with complex and varied symptoms.
  • Cluster analysis has been utilized to explore these symptom patterns and identify patient subgroups.

Purpose of the Study:

  • To systematically review and synthesize existing research on cluster analysis in Fibromyalgia syndrome.
  • To identify common variables, methods, patient subgroups, and evaluation metrics used in FMS cluster studies.

Main Methods:

  • A systematic review adhering to PRISMA guidelines was conducted.
  • Searches were performed across major databases (PubMed, Embase, Web of Science, Cochrane Central) for studies published up to January 2024.
  • Included studies used cluster analysis to examine physical, psychological, clinical, or biomedical variables in FMS patients.

Main Results:

  • 39 studies were included, predominantly using cross-sectional designs.
  • Identified patient profiles varied, including 2-4 severity/adjustment levels, 2-3 symptom-based clusters (pain vs. fatigue, pain sensitivity), and personality/psychological vulnerability profiles.
  • Different responses to pharmacological and multimodal treatments were also observed across clusters.

Conclusions:

  • The existence of distinct patient profiles within FMS underscores the necessity for personalized treatment strategies.
  • Efficient allocation of healthcare resources can be improved by recognizing these subgroups.
  • Further research is recommended to validate cluster findings and explore more objective measurement tools.