Arthritis & Rheumatism, Volume 60,
October 2009 Abstract Supplement
The 2009 ACR/ARHP Annual Scientific Meeting
Philadelphia October 16-21, 2009.
Towards Development of Fibromyalgia Responder Index: Identifying Responders Using Patients Global Assessment
Arnold1, Lesley M., Zlateva2, Gergana, Sadosky2, Alesia, Emir2, Birol, Whalen2, Ed, Scott3, Gayle
The Fibromyalgia (FM) Working Group of OMERACT is developing an FM responder index. Towards that objective, we conducted an analysis of pooled data from pregabalin fibromyalgia trials to determine what FM domains drive patients' perception of improvement.
Data from 3 double-blind, placebo-controlled trials of pregabalin monotherapy (1314 weeks) in FM conducted in North and South America, Europe, and Asia were pooled for this analysis. We analyzed changes in independent variables, including the Short-Form 36 (SF-36) health survey scale, Medical Outcomes Study (MOS) sleep scale, sleep quality score from the daily sleep diary, pain score from the daily pain diary, Fibromyalgia Impact Questionnaire (FIQ), and Multidimensional Assessment of Fatigue (MAF) as predictors of outcome on the dependent variable PGIC. Correlation analysis was used to assess the strength and direction of relationship between the independent variables and PGIC. Cluster analysis was conducted using Hoeffding's D similarity measure to identify dependencies or clustering among variables. Finally, a LASSO (least absolute shrinkage and selection operator) technique was used to derive rank order among the independent variables most highly related to changes in PGIC.
1664 patients were included in the intention-to-treat population of these pooled analyses. More than 90% were white women, and mean age was 49 years. In each of the treatment groups (pregabalin 300 mg/day, 450 mg/day, and placebo), improvement in PGIC at endpoint showed highest correlation with improvement in pain, fatigue, sleep, and work and physical function (0.4< r <0.6). Mood, emotional and social functioning generally had smaller correlation with PGIC (0.3 < r <0.4). When pooled, the combined treatment groups showed similarly moderate correlation between PGIC and pain, fatigue, sleep, and function. Cluster analysis identified 5 main clusters of symptoms in FM patients at endpoint: emotion, function, tiredness, pain, and sleep. LASSO analysis ranked 3 pain variables (pain diary score, FIQ Pain, and SF-36 Bodily Pain) as the most important variables explaining variability in PGIC, followed by MAF Global Fatigue Index, MOS Sleep Disturbance, FIQ Feel Good, SF-36 Vitality and FIQ Rested domains. LASSO results were similar by dose and across the pooled analysis.
Patients' response to FM treatment was driven by improvement of multiple domains. Pain, fatigue and sleep associate most strongly with improvement in PGIC. Physical and work-related function also correlate with patients overall assessment of improvement. These domains and their respective outcome measures can be used in the development of a responder index.
To cite this abstract, please use the following information:
Arnold, Lesley M., Zlateva, Gergana, Sadosky, Alesia, Emir, Birol, Whalen, Ed, Scott, Gayle; Towards Development of Fibromyalgia Responder Index: Identifying Responders Using Patients Global Assessment [abstract]. Arthritis Rheum 2009;60 Suppl 10 :1424