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Introduction Rheumatoid arthritis (RA) composite disease activity indices have become handy tools in daily clinical practice and crucial in defining remission or low disease activity, the main target of the RA treatment. However, there is no definition of the best index to assess disease activity in clinical practice. Objectives To compare the residual activity among the indices with the ACR/EULAR remission criteria (Boolean method) to identify the most feasible for assessing remission in daily practice, also considering correlation and concordance, sensibility, and specificity. Patients and methods We selected 1116 patients with established RA from the real-life rheumatoid arthritis study database—REAL. The composite disease activity indices—DAS28-ESR, DAS28-CRP, SDAI, and CDAI–and their components were compared to the Boolean method to identify residual activity using binomial regression. The indices were analyzed for correlation and agreement using the Spearman index and weighted kappa. The chi-square test evaluated sensibility and specificity for remission based on the Boolean method. Results DAS28-CRP overestimated remission and confirmed higher residual activity than SDAI and CDAI. The indices showed good correlation and agreement, with a better relationship between SDAI and CDAI (k:0,88). CDAI and SDAI showed higher sensitivity and specificity for remission based on the Boolean method. CDAI was performed in 99% of patients, while DAS28 and SDAI were completed in approximately 85%. Conclusions Although all composite indices of activity can be used in clinical practice and showed good agreement, CDAI and SDAI have better performance in evaluating remission based on the Boolean method, showing less residual activity and higher sensibility and specificity. In addition, CDAI seems to be more feasible for disease activity evaluation in daily clinical practice, especially in developing countries.

Background Discordance between patient’s global assessment (PtGA) and physician’s global assessment (PhGA) has been described in rheumatoid arthritis (RA). Understanding the reasons for this discrepancy is important in the context of treat-to-target treatment strategy. Objective To assess the determinants of PtGA and PhGA and factors associated with discordance between them. Methods The REAL study included RA patients from Brazilian public health centers. Clinical, laboratory and outcomes measures were collected. PtGA and the PhGA were rated on a visual analog scale and analyzed. Three groups were defined: no discordance (difference between PtGA and PhGA within 3 cm), positive discordance (PtGA exceeding PhGA by >3 cm), and negative discordance (PtGA less than PhGA by >3 cm). Multivariate regression analysis was used to identify determinants of PtGA and PhGA and their discordance. Results 1115 patients (89,4% female, mean age 56.7y and median disease duration of 12.7y) were enrolled. Two factors were associated with PtGA in the final multivariate model: one point increase in the pain scale leads to an increase of 0.62 in PtGA; one point increase in HAQ increases by 9,25 points the PtGA. The factors associated with PhGA were pain scale, number of tender and swollen joints (NTJ and NSJ), positive RF, ESR, HAQ-DI and use of corticosteroids. Discordance between patient and physician was found in 30.52%: positive discordance in 24.6% and negative discordance in 5.92%. An increase of one point in the NSJ was associated with a 12% increase in the chance of negative discordance. The chance of positive discordance increased by 90% and 2% for each unit increased in HAQ-DI and pain scale respectively. Finally, the chance of positive discordance decreased by 3% for each point increased in NTJ and by 15% for each point increased in NSJ. Conclusion In one-third of the assessments, there was disagreement between PtGA and PhGA (a positive discordance was found in 80% of them). Pain and function were determinants for patients to estimate disease activity, while swollen joints was the main factor related to a worse physician’s evaluation. These data show how different can be the perspectives of patients and assistants.