RT Journal Article SR Electronic T1 Do We Need Core Sets of Fibromyalgia Domains? The Assessment of Fibromyalgia (and Other Rheumatic Disorders) in Clinical Practice JF The Journal of Rheumatology JO J Rheumatol FD The Journal of Rheumatology SP jrheum.100511 DO 10.3899/jrheum.100511 A1 Frederick Wolfe A1 Afton L. Hassett A1 Robert S. Katz A1 Kaleb Michaud A1 Brian Walitt YR 2011 UL http://www.jrheum.org/content/early/2011/01/27/jrheum.100511.abstract AB Objective An OMERACT consensus process recommended domains for investigation in fibromyalgia (FM) clinical trials. We used patient data to investigate variable importance in the determination of patient global and health-related quality of life (HRQOL) in FM and non-FM patients to determine whether variables were valued differently in FM compared with non-FM states. Methods We used ACR 2010 diagnostic FM criteria modified for epidemiological and clinical research to identify patients with rheumatoid arthritis (RA; N = 5884) with and without FM, and also characterized previously diagnosed patients with FM (N = 808) as to current criteria status. We measured variable importance by multivariable regression, decomposing regression variance by averaging over model orderings. We examined the distributions of key variables in the various disorders, and the distributions as a function of a FM severity index (fibromyalgianess). Results Out of 9 measures, pain, Health Assessment Questionnaire disability index, and fatigue explained more than 50% of explainable variance (50.49%–56.59%). Explained variance was similar across all disorders and diagnostic groups. In addition, the SF-36 physical component summary score varied across disorders as a function of fibromyalgianess. Conclusion The main determinants of global severity and HRQOL in FM are pain, function, and fatigue. But these variables are also the main determinants in RA and other rheumatic diseases. The content and impact of FM, whether measured by discrete variables or a fibromyalgianess scale, seems to be independent of diagnosis. These data argue for a common set of variables rather than disease-specific variables. Clinical use is supported and enhanced by simple measures.