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Functional Status, Quality of Life, and Costs Associated With Fibromyalgia Subgroups

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Objectives:

Although fibromyalgia syndrome (FM) is considered a heterogeneous condition, there is no generally accepted subgroup typology. We used hierarchical cluster analysis and latent profile analysis to replicate Giesecke’s classification in Spanish FM patients. The second aim was to examine whether the subgroups differed in sociodemographic characteristics, functional status, quality of life, and in direct and indirect costs.

Materials and Methods:

A total of 160 FM patients completed the following measures for cluster derivation: the Center for Epidemiological Studies-Depression Scale, the Trait Anxiety Inventory, the Pain Catastrophizing Scale, and the Control over Pain subscale. Pain threshold was measured with a sphygmomanometer. In addition, the Fibromyalgia Impact Questionnaire-Revised, the EuroQoL-5D-3L, and the Client Service Receipt Inventory were administered for cluster validation.

Results:

Two distinct clusters were identified using hierarchical cluster analysis (“hypersensitive” group, 69.8% and “functional” group, 30.2%). In contrast, the latent profile analysis goodness-of-fit indices supported the existence of 3 FM patient profiles: (1) a “functional” profile (28.1%) defined as moderate tenderness, distress, and pain catastrophizing; (2) a “dysfunctional” profile (45.6%) defined by elevated tenderness, distress, and pain catastrophizing; and (3) a “highly dysfunctional and distressed” profile (26.3%) characterized by elevated tenderness and extremely high distress and catastrophizing. We did not find significant differences in sociodemographic characteristics between the 2 clusters or among the 3 profiles. The functional profile was associated with less impairment, greater quality of life, and lower health care costs.

Discussion:

We identified 3 distinct profiles which accounted for the heterogeneity of FM patients. Our findings might help to design tailored interventions for FM patients.

Keywords: cluster analysis; fibromyalgia subgroups; latent profile analysis

Document Type: Research Article

Affiliations: 1: Teaching, Research and Innovation Unit, Parc Sanitari Sant Joan de Déu, Primary Care Prevention and Health Promotion Research Network (RedIAPP, ISCIII) 2: Health Services Research Group, IMIM (Hospital del Mar Medical Research Institute), Biomedical Research Center Network for Epidemiology and Public Health (CIBERESP, ISCIII, Madrid, Spain) 3: Teaching, Research and Innovation Unit, Parc Sanitari Sant Joan de Déu 4: Primary Care Prevention and Health Promotion Research Network (RedIAPP, ISCIII), Primary Health Centre Bartomeu Fabrés Anglada, SAP Delta Litoral, DAP Costa de Ponent, Institut Català de la Salut, Gavà 5: Primary Care Prevention and Health Promotion Research Network (RedIAPP, ISCIII), Primary Health Centre Bartomeu Fabrés Anglada, SAP Delta Litoral, DAP Costa de Ponent, Institut Català de la Salut, Gavà 6: Primary Care Prevention and Health Promotion Research Network (RedIAPP, ISCIII), Department of Psychiatry and Physiotherapy, Faculty of Medicine, Malaga University, Malaga 7: Rheumatology Service, Hospital de Viladecans, Institut Català de la Salut, Viladecans, Barcelona 8: Rheumatology Service, Parc Sanitari Sant Joan de Déu, Sant Boi de Llobregat 9: Primary Care Prevention and Health Promotion Research Network (RedIAPP, ISCIII), Department of Psychiatry, Miguel Servet Hospital, Aragon Institute of Health Sciences (I+CS), Zaragoza, Spain

Publication date: 01 October 2016

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