POS0222 PREDICTORS OF RESPONSE: BASELINE CHARACTERISTICS AND EARLY TREATMENT RESPONSES ASSOCIATED WITH ACHIEVEMENT OF REMISSION AND LOW DISEASE ACTIVITY AMONG UPADACITINIB-TREATED PATIENTS WITH RHEUMATOID ARTHRITIS

Background: Upadacitinib (UPA) 15 mg once daily (QD) has demonstrated efficacy in phase 3 studies of patients with rheumatoid arthritis (RA).1–4 Early prediction of response to treatment with UPA could help to optimize therapy. Objectives: To identify baseline (BL) characteristics or Week (Wk) 12 disease activity measures that may predict the achievement of remission (REM) or low disease activity (LDA) at 6 months in patients with RA receiving UPA 15 mg. Methods: This ad hoc analysis included patients who were randomized to UPA 15 mg QD, as monotherapy in methotrexate (MTX)-naïve patients (SELECT-EARLY) or in combination with conventional synthetic disease-modifying antirheumatic drugs (csDMARDs), in patients with an inadequate response (IR) to MTX (SELECT-COMPARE) or ≥1 tumor necrosis factor inhibitors (TNFis) (SELECT-BEYOND and SELECT-CHOICE). The association of BL characteristics (including age, disease duration, prior/concomitant treatments, C-reactive protein [CRP], seropositivity, and disease activity) and Wk 12 disease activity parameters with the achievement of Clinical Disease Activity Index (CDAI) REM (≤2.8) or LDA (≤10) at Wk 24 (or Wk 26 in SELECT-COMPARE) was assessed by concordance statistics (C-statistics), or area under the receiver operator characteristic curve. C-index values and 95% confidence intervals were calculated by fitting a univariate logistic regression model for: demographic and BL characteristics, Wk 12 disease activity measures, and change from BL at Wk 12 in disease activity measures. A multivariate logistic regression with stepwise model selection was also performed. The proportion of patients achieving Wk 24/26 CDAI REM/LDA was stratified by ≥50% improvement from BL in swollen and/or tender joint count in 66/68 joints (SJC66/TJC68). Results: A total of 1377 patients were included in the analysis. Across the 4 studies, CDAI REM and LDA were achieved in 11.0–28.4% and 50.0–58.6% of patients, respectively (Table 1). BL demographics and disease characteristics were weakly predictive (C-index <0.70) of Wk 24/26 CDAI REM (C-index 0.49–0.69) or LDA (C-index 0.47–0.65), with the exception of BL Health Assessment Questionnaire-Disability Index in SELECT-BEYOND, which was moderately predictive of CDAI REM (C-index 0.73). Changes from BL in disease activity measures at Wk 12 were weakly or moderately predictive of Wk 24/26 CDAI REM (Figure 1) or LDA. CDAI value at Wk 12 was strongly predictive (C-index >0.80) of Wk 24/26 CDAI REM or LDA. Disease Activity Score in 28 joints using CRP and pain at Wk 12 were strongly predictive of Wk 24/26 CDAI REM (except in SELECT-CHOICE). Physician’s global assessment at Wk 12 was the only common predictor in the multivariate regression models for CDAI REM/LDA at Wk 24/26 across the 4 studies. A greater proportion of patients achieving ≥50% improvement in SJC66 and TJC68 at Wk 12 achieved CDAI REM (16.5–37.8% vs 0–9.4%) or LDA (66.0–72.8% vs 20.9–35.7%) at Wk 24/26 than those who did not. Table 1. Achievement of CDAI LDA and REM at Wk 24/26 a SELECT-EARLY SELECT-COMPARE SELECT-BEYOND SELECT-CHOICE Patient population MTX-naïve MTX-IR TNFi-IR TNFi-IR Treatment UPA 15 mg monotherapy (n=317) UPA 15 mg + MTX (n=651) UPA 15 mg + csDMARD (n=146) UPA 15 mg + csDMARD (n=263) Efficacy at Wk 24/26 a , n (% ) CDAI REM (≤2.8) 90 (28.4) 150 (23.0) 16 (11.0) 60 (22.8) CDAI LDA (≤10) 178 (56.2) 343 (52.7) 73 (50.0) 154 (58.6) a Wk 26 for SELECT-COMPARE only Conclusion: BL characteristics did not strongly predict response to UPA, but composite disease activity scores at Wk 12 predicted Wk 24/26 REM/LDA with UPA 15 mg QD across MTX-naïve, MTX-IR, and TNFi-IR patients. ≥50% improvement in SJC/TJC at Wk 12 was also associated with Wk 24/26 REM/LDA. References: [1]van Vollenhoven R, et al. Arthritis Rheumatol 2020;72:1607–20; 2. Genovese MC, et al. Lancet 2018;391:2513–24; 3. Fleischmann R, et al. Arthritis Rheumatol 2019;71:1788–800; 4. Rubbert-Roth A, et al. N Engl J Med 2020;383:1511–21. Acknowledgements: AbbVie funded this study; contributed to its design; participated in data collection, analysis, and interpretation of the data; and participated in the writing, review, and approval of the abstract. No honoraria or payments were made for authorship. Medical writing support was provided by Laura Chalmers, PhD, of 2 the Nth (Cheshire, UK), and was funded by AbbVie. Disclosure of Interests: Arthur Kavanaugh Consultant of: Janssen, Grant/research support from: Janssen, Zoltán Szekanecz: None declared, Edward C. Keystone Speakers bureau: Abbott, Amgen, AstraZeneca, Biotest, Bristol-Myers Squibb, Eli Lilly, Genentech, Janssen, MSD, Novartis, Pfizer, Roche, Sanofi, and UCB, Consultant of: Abbott, Amgen, AstraZeneca, Biotest, Bristol-Myers Squibb, Eli Lilly, Genentech, Janssen, MSD, Novartis, Pfizer, Roche, Sanofi, and UCB, Grant/research support from: Abbott, Amgen, AstraZeneca, Biotest, Bristol-Myers Squibb, Eli Lilly, Genentech, Janssen, MSD, Novartis, Pfizer, Roche, Sanofi, and UCB, Andrea Rubbert-Roth Consultant of: AbbVie, Amgen, Bristol-Myers Squibb, Chugai, Eli Lilly, Janssen, Novartis, Pfizer, Roche, and Sanofi, Stephen Hall Grant/research support from: Pfizer, Ricardo Xavier: None declared, Joaquim Polido-Pereira: None declared, In-Ho Song Shareholder of: May own stock or options in AbbVie, Employee of: AbbVie, Naomi Martin Shareholder of: May own stock or options in AbbVie, Employee of: AbbVie, Yanna Song Shareholder of: May own stock or options in AbbVie, Employee of: AbbVie, Samuel Anyanwu Shareholder of: May own stock or options in AbbVie, Employee of: AbbVie, Peter Nash Grant/research support from: AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly, Gilead, Janssen, MSD, Novartis, Pfizer, Roche, Sanofi, and UCB.