Reliability of a 1-week recall period for the Medical Outcomes Study Sleep Scale (MOS-SS) in patients with fibromyalgia

<p>Abstract</p> <p>Objective</p> <p>To evaluate the reliability of a one-week versus a four-week recall period of the Medical Outcomes Study Sleep Scale (MOS-SS) in patients with fibromyalgia (FM).</p> <p>Methods</p> <p>The MOS-SS was administered by mail to patients with a confirmed diagnosis of FM and a current pain rating of > 2 (0–10 point numerical rating scale) recruited through newspapers, support groups, and the Internet. Reliability of MOS-SS subscale domains was evaluated using test-retest methodology separated by a 1–3 day interval for the 4-week recall period and a 7-day interval for the 1-week recall period. Patient Impression of Change was evaluated for sleep, and for patients with no change, the intraclass correlation coefficient (ICC) and the Pearson correlation coefficient was calculated for MOS-SS subscales.</p> <p>Results</p> <p>Of 129 patients enrolled, 91.3% were female, mean age was 49.4 ± 11.0 years; self-rated FM severity was moderate-to-severe in 88.1% of patients. MOS-SS subscale scores were similar for both recall periods with little variation between test-retest. The 9-item Sleep Problems Index scores ranged from 57.2 ± 14.5 to 61.9 ± 15.8 across all assessments and demonstrated high reliability which was similar for the 1-week (ICC 0.81) and 4-week (ICC 0.89) recall periods. For the other MOS-SS subscales, the 1-week recall period also showed good reliability, which was consistent for the ICC and Pearson correlation coefficients.</p> <p>Conclusion</p> <p>A 1-week recall period is adequately reliable for use of the MOS-SS in studies evaluating sleep disturbance in patients with FM.</p

Identification of symptom and functional domains that fibromyalgia patients would like to see improved: a cluster analysis

<p>Abstract</p> <p>Background</p> <p>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.</p> <p>Methods</p> <p>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.</p> <p>Results</p> <p>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).</p> <p>Conclusion</p> <p>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.</p