Background: Fibromyalgia (FM) is a heterogeneous complex condition. Its cardinal feature is chronic widespread pain but the associated symptoms such as fatigue, insomnia, anxiety and depression are common. Many methods are used for the management of FM.
Objectives: The aim of the study is to compare FM patients with Rheumatoid Arthritis (RA) patients and healthy controls with respect to standard evaluation criteria, pain and psychological measures in a case control design.
Methods: In this study 40 patients with FM, 40 patients with RA and 40 patients with sex- and age matched healthy controls participated. The demographic characteristics including age, body mass index, duration of disease and tender point count (TPC) were recorded. Several instruments were used: Fibromyalgia Impact Questionnaire (FIQ) to assess quality of life, Beck Depression Inventory (BDI) for depression, STAI for anxiety and to assess pain the visual analog scala (VAS). ROC (Receiver operating characteristic curves) analysis were performed to test whether higher levels of measures are associated with one disease rather than another, or with one disease rather than healthy controls. For each regression model, the best exploratory covariates were determined using receiver operating characteristic (ROC) curves.
Results: All groups were statistically similar in terms of the demographic characteristics as seen in Table 1 (p>0.05). In the logistic regression model where for FM cases vs. RA cases, the VAS (pain), the FIQ, the TPC, the BDI and the STAI-I STAI-II were taken as covariates; the BDI, STAI-I and STAI-II covariates were found to be non-significant. In ROC curve analysis the most important co-variate was found to be the TPC and area under the curve (AUC) was 0.932. In the logistic regression model for FM cases vs. healthy controls, with STAI-I and STAI-II were not significant and AUC was 0.951 for TPC. A cut-off score for TPC of 6 gave a sensitivity of 0.970 and specificity of 0.900. In the logistic regression model for RA cases vs. healthy controls where the VAS, TPC, FIQ, BDI, STAI-I and STAI-II were taken as co-variates, the STAI-I variable was found to be non-significant whereas the VAS, TPC, FIQ, BDI and STAI-II variables were significant. After the ROC curve analysis the most important co-variate was found to be the FIQ (AUC =0.779).
Table:

Demographics characteristics of study and control groups
	FMS n=40 Mean ± SD	RA n=40 Mean ± SD	Controls n =40 Mean ± SD
Age (years)*	42.25 ± 8.02	42.60 ± 9.95	41.25 ± 7.43
BDI	14.17 ± 7.10	13.27 ± 6.47	9.52 ± 8.85
STAI-I	47.37 ± 9.53	45.20 ± 9.52	41.37 ± 9.83
STAI-II	49.45 ± 9.40	47.90 ± 6.72	44.25 ± 10.55
VAS	6.95 ± 2.18	4.80 ± 2.13	2.85 ± 2.73
TPC	12.40 ± 3.20	5.25 ± 3.43	3.22 ± 3.24
FIQ	50.52 ± 13.20	36.35 ± 12.70	21.90 ± 14.60
BMI*	25.46 ± 3.45	26.17 ± 4.80	24.70 ± 4.41
Duration of illness (years)	5.87 ± 5.16	8.70 ± 7.54	-
* (p>0.05)

Conclusion: The VAS and TPC may be more sensitive indicator of diagnosis and clinical change in FM than either psychological measures. Depression and anxiety is not specific to FM patients. Furthermore FIQ should be re-evaluated for the specificity and sensitivity for the used in FM.
References: 1. Sayar K, Gulec H, Topbas M, Kalyoncu A. Affective distress and fibromyalgia. Swiss Med Wkly. 2004;134:248-53.
2. Dewalt DEA, Reed GW, Pincus T. Further clues to recognition of patients with fibromyalgia from a simple 2-page patients multidimensional health assessment questionnaire (MDHAQ). Clin Exp Rheumatol 2004;22:453-61.