AB0293 Factors Influencing Physician Global Assessment of Rheumatoid Arthritis Disease Activity in Usual Clinical Practice

Background Patient global assessment (PATGL) and physician global assessment (PhGL) of disease status are 2 of the 7 rheumatoid arthritis (RA) core data set measures. Several reports indicate considerable discordance between PATGL and PhGL [1]. Variation in PhGL appears to be explained by different factors in discordant patient group comparing with concordant group. Objectives To analyze variation in PhGL by examination of possible associations with all RA core data set measures, rheumatoid factor (RF) and anti-citrullinated protein antibodies (ACPA), in patients monitored in usual care in a Korean rheumatology setting. Methods A cross-sectional study was conducted of patients with RA seen by 4 rheumatologists in a Korean usual care setting. All core data set measures, as well as RF and ACPA, are collected in each RA patient. A tender joint count (TJC28) and swollen joint count (SJC28) are performed on each patient, and laboratory tests – erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), RF and ACPA – are obtained. A PhGL is assigned by the rheumatologist after review of all data. All study population was divided in three groups: positive discordance; PATGL-PhGL>1, no discordance; -1≤PATGL-PhGL≤1, negative discordance; PATGL-PhGL<-1. In each group, correlations of all core data set measures, as well as RF and ACPA, with PhGL were analyzed using Spearman9s rho. Univariate and multivariate regressions were performed for each measure with PhGL as the dependent variable, and core data set measures and laboratory tests as independent variables. Results The study population was 89.2% female, with median age 55.0 years. PhGL was correlated significantly with all 7 core data set measures (Spearman9s rho 0.236-0.356, p<0.001). PhGL was not correlated significantly with RF and ACPA. 270 patients (53.8%) were positively discordant and median disease activity score (DAS)28 was 3.9. TJC28, pain, PATGL, PhGL, DAS28 was significantly different between 3 groups. By multivariate regression, PhGL was associated independently with TJC28, PATGL and ESR in positive discordance group. TJC did not influence PhGL in concordant group. If a RF level was high, physicians seemed to rate disease activity higher than patients in negative discordant group. Conclusions PhGL is correlated significantly with all RA core data set measures. In multivariate regressions, PhGL was associated significantly with TJC28, PATGL, ESR and RF, but not with SJC28, physical function or pain score. These findings are consistent with other reports in the literature. Further research is needed to clarify the basis for variation in PhGL and concordance or discordance with PATGL. References Barton JL, Imboden J, Graf J, et al. Arthritis Care Res 2010;62:857-64 Disclosure of Interest None declared DOI 10.1136/annrheumdis-2014-eular.3450