TY - JOUR
T1 - Identification of symptom and functional domains that fibromyalgia patients would like to see improved
T2 - A cluster analysis
AU - Bennett, Robert M.
AU - Russell, Jon
AU - Cappelleri, Joseph C.
AU - Bushmakin, Andrew G.
AU - Zlateva, Gergana
AU - Sadosky, Alesia
N1 - Funding Information:
This study was funded by Pfizer Inc, the manufacturer of pregabalin. The data for these analyses were obtained from a clinical trial sponsored by Pfizer Inc (NCT00333866). RMB and IJR are paid consultants to Pfizer Inc, and IJR was an investigator on the clinical study. IJR is also supported in part by a grant from the RGK Foundation of Austin Texas. JCC, AS, GZ and AGB are employees and shareholders of Pfizer Inc. Editorial support was provided by E. Jay Bienen, who was funded by Pfizer Inc.
PY - 2010
Y1 - 2010
N2 - Background. The purpose of this study was to determine whether some of the clinical features of fibromyalgia (FM) that patients would like to see improved aggregate into definable clusters. Methods. Seven hundred and eighty-eight patients with clinically confirmed FM and baseline pain 40 mm on a 100 mm visual analogue scale ranked 5 FM clinical features that the subjects would most like to see improved after treatment (one for each priority quintile) from a list of 20 developed during focus groups. For each subject, clinical features were transformed into vectors with rankings assigned values 1-5 (lowest to highest ranking). Logistic analysis was used to create a distance matrix and hierarchical cluster analysis was applied to identify cluster structure. The frequency of cluster selection was determined, and cluster importance was ranked using cluster scores derived from rankings of the clinical features. Multidimensional scaling was used to visualize and conceptualize cluster relationships. Results. Six clinical features clusters were identified and named based on their key characteristics. In order of selection frequency, the clusters were Pain (90%; 4 clinical features), Fatigue (89%; 4 clinical features), Domestic (42%; 4 clinical features), Impairment (29%; 3 functions), Affective (21%; 3 clinical features), and Social (9%; 2 functional). The "Pain Cluster" was ranked of greatest importance by 54% of subjects, followed by Fatigue, which was given the highest ranking by 28% of subjects. Multidimensional scaling mapped these clusters to two dimensions: Status (bounded by Physical and Emotional domains), and Setting (bounded by Individual and Group interactions). Conclusion. Common clinical features of FM could be grouped into 6 clusters (Pain, Fatigue, Domestic, Impairment, Affective, and Social) based on patient perception of relevance to treatment. Furthermore, these 6 clusters could be charted in the 2 dimensions of Status and Setting, thus providing a unique perspective for interpretation of FM symptomatology.
AB - Background. The purpose of this study was to determine whether some of the clinical features of fibromyalgia (FM) that patients would like to see improved aggregate into definable clusters. Methods. Seven hundred and eighty-eight patients with clinically confirmed FM and baseline pain 40 mm on a 100 mm visual analogue scale ranked 5 FM clinical features that the subjects would most like to see improved after treatment (one for each priority quintile) from a list of 20 developed during focus groups. For each subject, clinical features were transformed into vectors with rankings assigned values 1-5 (lowest to highest ranking). Logistic analysis was used to create a distance matrix and hierarchical cluster analysis was applied to identify cluster structure. The frequency of cluster selection was determined, and cluster importance was ranked using cluster scores derived from rankings of the clinical features. Multidimensional scaling was used to visualize and conceptualize cluster relationships. Results. Six clinical features clusters were identified and named based on their key characteristics. In order of selection frequency, the clusters were Pain (90%; 4 clinical features), Fatigue (89%; 4 clinical features), Domestic (42%; 4 clinical features), Impairment (29%; 3 functions), Affective (21%; 3 clinical features), and Social (9%; 2 functional). The "Pain Cluster" was ranked of greatest importance by 54% of subjects, followed by Fatigue, which was given the highest ranking by 28% of subjects. Multidimensional scaling mapped these clusters to two dimensions: Status (bounded by Physical and Emotional domains), and Setting (bounded by Individual and Group interactions). Conclusion. Common clinical features of FM could be grouped into 6 clusters (Pain, Fatigue, Domestic, Impairment, Affective, and Social) based on patient perception of relevance to treatment. Furthermore, these 6 clusters could be charted in the 2 dimensions of Status and Setting, thus providing a unique perspective for interpretation of FM symptomatology.
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U2 - 10.1186/1471-2474-11-134
DO - 10.1186/1471-2474-11-134
M3 - Article
C2 - 20584327
AN - SCOPUS:77953941540
SN - 1471-2474
VL - 11
JO - BMC musculoskeletal disorders
JF - BMC musculoskeletal disorders
M1 - 134
ER -