Background/Purpose: Rheumatoid Arthritis (RA) treatment targets remission or low disease activity, thus reducing the disease impact in patients’ lives. Assessing different tools for effectiveness (disease activity, functional status and utility) could provide a more comprehensive approach in term of “achieve and maintain” the therapeutic goal. The aim of the present study is to evaluate interrelations of disease activity score – functional status – utility in a cohort of RA patients, treated with tumor necrosis factor alpha (TNF) antagonists and anti CD20 molecule.

Methods: Observational study in a cohort of RA patients in Romania, where data was gathered from the Romanian Registry of Rheumatic Diseases, which comprises all RA patients treated with biologics in the country. The three main variables under study were EQ5D (for utility), HAQ score (for functional status) and DAS28 and SDAI (for disease activity). The study cohort included only RA patients for whom were available all these data. The interrelations of the efficacy parameters were analyzed using correlation tests, T test, ANOVA, linear regression.

Results: The cohort included 777 RA patients, mean age 58.72 (±12.37) yrs, 84.4% women, mean RA duration 14.08 (±8.33) yrs, 77.1% retired, treated with etanercept (30.6%), adalimumab (22.7%), infliximab (original 6.3%, biosimilars 0.7%), rituximab (26.3%). 27.3% used steroids (20.2% with <7.5mg prednisone daily); mean current DAS28 score =3.66 (±1.52), mean ∆DAS28= 0.13 (±1.28), mean SDAI =14.27 (±13.79), mean HAQ score =1.14 (±0.64), mean EQ5D= 0.61±0.31. There was a strong negative association between DAS28 (and SDAI) and EQ5D: r = – 0.7 (p<0.001). HAQ score positively correlates with DAS28, same as with SDAI: r = 0.5 (p<0.001) whereas is a negative association between HAQ and EQ5D: r = – 0.6 (p<0.001). Disease activity dynamics (∆ DAS28 for the last 6 months) had a mild association with HAQ: r = 0.1 (p<0.05) and a negative one with EQ5D: r = -0.2 (p<0.01). Patient global assessment (PGA) on disease activity had a significant association both with HAQ (r=0.6, p<0.001) and EQ5D (r = – 0.6, p<0.01). Analyzing distribution of EQ5D and HAQ in DAS28 categories, there was a significant difference between categories (p<0.001); for EQ5D – DAS28: <2.6= 0.81(±.19), 2.6-3.2= 0.68(±.17), 3.2-5.1= 0.63(±.18), >5.1= 0.16(±.38); for HAQ – DAS28: <2.6= 0.73(±.57), 2.6-3.2= 0.98(±.5), 3.2-5.1= 1.25(±.52), >5.1= 1.76(±.56). There are significant predictive relations between DAS28, HAQ and EQ5D: linear regression model showed that DAS28 is strongly predicted by EQ5D (F = 798.7, t = -28.2, B = – 3.48, p<0.0001), over than 50% of the variability of DAS28 being determined by the variability of EQ5D (adjusted R square = 0.51). HAQ score has a predictive value for DAS28 (F = 341.6, t = 18.4, B = 1.32, p<0.0001), roughly 30% of the variability of DAS28 being determined by the variability of HAQ (adjusted R square = 0.30). Disease duration had not any influence on EQ5D, HAQ or DAS28.

Conclusion: Disease activity influences the patient well-being and functional status. Regression model showed that DAS28 could be predicted by the evaluation of EQ5D and HAQ level, regardless the disease duration.

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ACR Meeting Abstracts - https://acrabstracts.org/abstract/importance-of-functional-and-utility-evaluation-on-disease-activity-level-in-rheumatoid-arthritis-interrelations-and-predictive-value/