Abstract: According to international recommendations, the Ankylosing Spondylitis Disease Activity Score (ASDAS) is the preferred score for assessing disease activity in axial spondyloarthritis (axSpA) [1]. However, routine determination of C-reactive protein (CRP) to calculate ASDAS values takes hours to days. This limits the use of ASDAS in clinical routine and clinical trials and hinders the implementation of treat-to-target approaches in axSpA. Whereas quick quantitative CRP (qCRP) tests allow CRP assessment within a few minutes. In a pilot project the performance of qCRP-based ASDAS assessment (ASDAS-qCRP) was already investigated in a single center study of 50 newly diagnosed, bDMARD-naïve axSpA patients with promising results [2] . Objectives: To validate the ASDAS-qCRP in a prospective, multicenter study of axSpA patients in a typical axSpA cohort with an appropriate sample size. Methods: The study was conducted in five centers in Germany. Consecutive adult (≥ 18 years) axSpA patients were included. In addition to a rheumatological assessment, including patient reported outcomes (PROs), routine CRP and erythrocyte sedimentation rate (ESR) were measured in the local labs. Additionally, a qCRP testing with the „QuikRead go instrument“ (Aidian Oy, Finland) was performed at the study center (measurement range 0.5 - 200 mg/l for hematocrit concentrations of 40 – 45%). Statistical analysis included descriptive statistics, cross tabulation and weighted Cohen´s kappa comparing disease activity categories, Bland-Altman plots and intraclass correlation coefficient (ICC) for ASDAS-CRP and ASDAS-qCRP. Results: In this study 251 axSpA patients were included between January and September 2020 (mean age: 38.4 years; mean disease duration: 6.2 years, 159 patients (63.3%) were male, 211 (84.1%) HLA-B27 positive and 195 (77.7%) were classified as radiographic axSpA). 143 patients (57.0%) were treated with bDMARDs. CRP and qCRP showed mean values of 2.12 and 2.17 mg/l, respectively. With the ASDAS-qCRP, 242 patients (96.4%) were assigned to the same disease activity category as compared to the ASDAS based on the conventional lab CRP measurement (Table 1). Weighted Cohen´s kappa was 0.966 (95%CI: 0.943; 0.988). ICC for ASDAS-CRP- and ASDAS-qCRP-values was 0.997 (95%CI: 0.994; 0.999). The agreement of ASDAS-qCRP and ASDAS-CRP is shown in a Bland-Altman plot (Figure 1). Table 1. Disease activity categories by ASDAS-qCRP vs. ASDAS-CRP ASDAS-qCRP (n = 251) Inactive Disease ( 〈 1.3) Low Disease Activity (1.3 - 〈 2.1) High Disease Activity (2.1 - 3.5) Very high Disease Activity ( 〉 3.5) ASDAS-CRP Inactive Disease ( 〈 1.3) 56 (22.3%) 2 (0.8%) Low Disease Activity (1.3 - 〈 2.1) 62 (24.7%) 7 (2.8%) High Disease Activity (2.1 - 3.5) 97 (38.6%) Very high Disease Activity ( 〉 3.5) 27 (10.8%) The fields highlighted in red indicate that disease activity categories do not match. ASDAS = Ankylosing Spondylitis Disease Activity Score, CRP = C-reactive protein, qCRP = quick quantitative CRP Conclusion: The ASDAS-qCRP and ASDAS-CRP showed an almost perfect agreement on the assignment to disease activity categories (96%) with the important advantage of time. With ASDAS-qCRP, rheumatologists could base their clinical decision-making on a disease activity measurement by using a composite score immediately. ASDAS-qCRP, therefore, can be integrated in clinical routine and clinical trials in the future and may facilitate implementation of the treat-to-target concept in axial SpA. References: [1]Smolen JS, et al. Ann Rheum Dis. 2018 Jan; 77(1):3-17. [2]Proft F, et al. Joint Bone Spine. 2019 Jul 29. Figure 1. Bland-Altman plot for ASDAS-qCRP and ASDAS-CRP Acknowledgements: The authors would like to deeply thank Braun T, Doerwald C, Deter N, Höppner C, Lackinger J, Lorenz C, Lunkwitz K, Mandt B, Sron S and Zernicke J for their practical support and coordinating the study. Funding statement: The AQUA study was supported by an unrestricted research grant from Novartis. Testing kits were provided free of charge from Aidian Oy, Finland. Disclosure of Interests: None declared

Abstract: Psoriatic arthritis (PsA) is a heterogeneous disease with multiple musculoskeletal and dermatological manifestations. Due to this multifaceted clinical appearance, international guidelines do not provide a clear recommendation for one specific score to assess disease activity in PsA [1]. The Disease Activity Index for Psoriatic Arthritis (DAPSA), a validated, unidimensional score focusing on joint involvement, is one of the recommended options [1] . However, routine determination of C-reactive protein (CRP) to calculate DAPSA values takes hours to days. In contrast, quick quantitative CRP (qCRP) tests require only a few minutes and might facilitate regular assessment of the DAPSA (as Q-DAPSA) in clinical routine. Objectives: To validate the Q-DAPSA in a prospective, multicenter study of PsA patients. Since the Disease Activity Score 28 (DAS28) is not only used in rheumatoid arthritis, but also in PsA patients, the study also investigated the performance of a qCRP based DAS28 (DAS28-qCRP) in a PsA cohort. Methods: The study was conducted in five centers in Berlin, Germany. Consecutive adult (≥ 18 years) PsA patients were included. In addition to a rheumatological assessment, including patient reported outcomes (PROs), routine CRP and erythrocyte sedimentation rate (ESR) were measured in the local labs. Additionally, a qCRP testing with the „QuikRead go instrument“ (Aidian Oy, Finland) was performed locally at the study center (measurement range 0.5 - 200 mg/l for hematocrit concentrations of 40 – 45%). Statistical analysis included descriptive statistics, cross tabulation and weighted Cohen´s kappa comparing disease activity categories, Bland-Altman plots and intraclass correlation coefficient (ICC) for DAPSA, Q-DAPSA, DAS28-CRP and DAS28-qCRP. Results: In this study 104 patients were included between January and October 2020 (mean age: 51.2 years, mean disease duration: 7.1 years, 49 patients (47.1%) were male). 53 patients (51.0%) were treated with a bDMARD and 37 patients (35.6%) with csDMARDs. CRP and qCRP showed mean values of 5.20 and 6.17 mg/l, respectively. With the Q-DAPSA, 103 patients (99.0%) were assigned to the same disease activity category when compared to DAPSA (Table 1). Weighted Cohen´s kappa was 0.990 (95%CI 0.970; 1.000). ICC for numerical values of DAPSA and Q-DAPSA was 1.000 (95%CI 0.999; 1.000). The agreement of Q-DAPSA and DAPSA is shown in a Bland-Altman plot (Figure 1). DAS28-CRP and -qCRP were available for 103 patients; 101 patients (98.1%) showed the same disease activity category in the DAS28-qCRP and weighted Cohen´s kappa was 0.951 (95%CI 0.886; 1.000). Conclusion: The Q-DAPSA and DAPSA showed an almost perfect agreement on the assignment to disease activity categories (99%) with the important advantage of time. With Q-DAPSA, rheumatologists could base their clinical decision-making on a disease activity measurement by using a composite score immediately. Consequently, Q-DAPSA can be integrated in clinical routine and clinical trials and could be implemented into the treat-to-target concept in PsA patients. For rheumatologists who prefer DAS28-CRP for assessing disease activity in PsA patients, DAS28-qCRP may serve as a suitable alternative. References: [1]Smolen JS, et al. Ann Rheum Dis. 2018 Jan; 77(1):3-17. Table 1. Disease activity categories by Q-DAPSA vs. DAPAS Q-DAPSA (n = 104 ) Remission (≤ 4) Low Disease Activity ( 〉 4 and ≤ 14) High Disease Activity ( 〉 14 and ≤ 28) Very high Disease Activity ( 〉 28) DAPSA Remission (≤ 4) 36 (34.6% ) 1 (1.0% ) Low Disease Activity ( 〉 4 and ≤ 14) 39 (37.5% ) High Disease Activity ( 〉 14 and ≤ 28) 22 (21.2% ) Very high Disease Activity ( 〉 28) 6 (5.8% ) The fields highlighted in red indicate that disease activity categories do not match. DAPSA = Disease activity index for Psoriatic Arthritis, Q-DAPSA = DAPSA calculated based on a quick quantitative CRP Figure 1. Bland-Altman plot for Q-DAPSA and DAPSA Acknowledgements: The authors would like to deeply thank Braun T, Doerwald C, Deter N, Höppner C, Lackinger J, Lorenz C, Lunkwitz K, Mandt B, Sron S and Zernicke J for their practical support and coordinating the study. Funding statement: The AQUA study was supported by an unrestricted research grant from Novartis. Testing kits were provided free of charge from Aidian Oy, Finland. Disclosure of Interests: None declared.

Abstract: Therapeutic decisions in RA patients should be based on regular disease activity assessment using scores like the Simplified Disease Activity Index (SDAI) or the Clinical Disease Activity Index (CDAI) [1]. The CDAI has the benefit of being immediately available, while the SDAI encompasses with the C-reactive protein (CRP) an acute phase reactant and therefore is the recommended score for the use in clinical trials. However, CRP determination takes hours to days, thus hindering the treat-to-target concept using the SDAI. Quick quantitative CRP (qCRP) tests allow CRP measurement within a few minutes. Therefore, qCRP based SDAI (SDAI-Q) could combine the advantages of both scores. Objectives: To validate the SDAI-Q in a prospective, multicenter study of RA patients. Methods: The study was conducted in five centers in Berlin, Germany. Consecutive adult (≥ 18 years) RA patients were included. In addition to a rheumatological assessment, including patient reported outcomes, routine CRP was measured in the local labs. Additionally, a qCRP testing with the „QuikRead go instrument“ (Aidian Oy, Finland) was performed locally (measurement range 0.5 - 200 mg/l). Statistical analysis included descriptive statistics, cross tabulation and weighted Cohen´s kappa comparing disease activity categories, Bland-Altman plots and intraclass correlation coefficient (ICC) for CRP, qCRP, SDAI, SDAI-Q and CDAI. Results: In this study 100 RA patients were included (mean age: 60.9 years, mean disease duration: 11.4 years, 73.0% were female, 63.0% RF positive, 57.0% ACPA positive, 49.0% positive and 29% negative for both parameters). 75.0% were treated with csDMARD, 15% with tsDMARDs, 39.0% with bDMARDs and 40% with glucocorticoids (mean prednisolone equivalent: 5.4 mg prednisolone/d). Mean CRP and qCRP-levels were 6.97 and 7.89 mg/l, respectively (ICC 0.992; 95%CI: 0.987; 0.995). Comparing SDAI-Q and SDAI, all patients (100%) achieved the same disease activity status (Table 1A); weighted Cohen´s kappa was 1.000 (95%CI: 1.000; 1.000). ICC for SDAI-Q- and SDAI-values was 1.000 (95%CI: 1.000; 1.000). The agreement of SDAI-Q and SDAI is shown in a Bland-Altman plot (Figure 1). When comparing the CDAI with the SDAI-Q 93 patients (93%) were assigned to the same disease activity category (Table 1B); weighted Cohen´s kappa was 0.929 (95%CI: 0.878; 0.981). ICC for numerical values of SDAI-Q and CDAI was 0.989 (95%CI: 0.978; 0.994). Conclusion: SDAI-Q showed an absolute agreement with SDAI on the assignment to disease activity categories with the important advantage of time. With SDAI-Q, rheumatologists could base their clinical decision-making immediately on an index-based disease activity measurement by using a composite score considering acute phase reactants. Consequently, SDAI-Q can be integrated in clinical routine and clinical trials and could be implemented into the treat-to-target concept in RA patients. References: [1]Smolen JS, et al. Ann Rheum Dis. 2016 Jan; 75(1):3-15. Table 1. A) Disease activity categories by SDAI-Q vs. SDAI; B) Disease activity categories by SDAI-Q vs. CDAI A SDAI-Q (n = 100 ) Remission (≤ 3.3) Low Disease Activity ( 〉 3.3 and ≤ 11) Moderate Disease Activity ( 〉 11 and ≤ 26) High Disease Activity ( 〉 26) SDAI Remission (≤ 3.3) 28 (28.0% ) Low Disease Activity ( 〉 3.3 and ≤ 11) 31 (31.0% ) Moderate Disease Activity ( 〉 11 and ≤ 26) 35 (35.0% ) High Disease Activity ( 〉 26) 6 (6.0% ) B SDAI-Q (n = 100 ) Remission (≤ 3.3) Low Disease Activity ( 〉 3.3 and ≤ 11) Moderate Disease Activity ( 〉 11 and ≤ 26) High Disease Activity ( 〉 26) CDAI Remission (≤ 2.8) 26 (26.0% ) Low Disease Activity ( 〉 2.8 and ≤ 10) 2 (2.0% ) 28 (28.0% ) 2 (2.0% ) Moderate Disease Activity ( 〉 10 and ≤ 22) 3 (3.0% ) 33 (33.0% ) High Disease Activity ( 〉 22) 6 (6.0% ) Fields highlighted in red indicate that disease activity categories do not match. SDAI = Simplified Disease Activity Index; SDAI-Q = SDAI calculated with a quick quantitative CRP assay; CDAI = Clinical Disease Activity Index. Figure 1. Bland-Altman plot for SDAI and SDAI-Q Acknowledgements The authors would like to deeply thank Braun T, Doerwald C, Deter N, Höppner C, Lackinger J, Lorenz C, Lunkwitz K, Mandt B, Sron S and Zernicke J for their practical support and coordinating the study. Funding statement: The AQUA study was supported by an unrestricted research grant from Novartis. Testing kits were provided free of charge from Aidian Oy, Finland. Disclosure of Interests: None declared

Abstract: There is some evidence that NSAIDs, in particular celecoxib (CEL), might possess not only symptomatic efficacy but also disease-modifying properties in radiographic axial spondyloarthritis (r-axSpA) formerly known as ankylosing spondylitis, retarding progression of structural damage in the spine if taken continuously. For biological disease-modifying antirheumatic drugs (bDMARDs), retardation of structural damage progression has also been demonstrated, but at least 4 years of treatment seem to be necessary (at least for tumour necrosis factor inhibitors – TNFi) to see such an effect. Therefore, a combination of an NSAID with a TNFi might bring additional benefits in terms of retardation of structural damage progression especially in high-risk patients. Objectives The aim of this RCT was to evaluate the impact of treatment with the COX-II-selective NSAID (CEL) when added to a TNFi (golimumab - GOL) compared with TNFi (GOL) alone on progression of structural damage in the spine over 2 years in patients with r-axSpA. Methods Eligible patients had r-axSpA and high disease activity (BASDAI ≥4), NSAID failure and risk factors for radiographic spinal progression: C-reactive protein 〉 5 mg/l and/or ≥1 syndesmophyte(s). The trial consisted of two phases: a 12-week run-in phase, in which all included patients received treatment with GOL 50 mg every 4 weeks sc, followed by a 96-week controlled treatment period, in which patients who achieved a BASDAI improvement of ≥2 points were randomly assigned to GOL + CEL 200 mg bid or GOL alone arms. The primary endpoint was radiographic spinal progression as assessed by the change in the modified Stoke Ankylosing Spondylitis Spine Score (mSASSS) after 108 weeks in the intent-to-treat population, read by 3 independent readers blinded for the treatment arm and the time-point. Results Of the 157 screened patients, 81.5% (n=128) were enrolled into the run-in phase. 109 patients fulfilled the BASDAI response criterion at w12 and were randomized 1:1 (54 vs. 55) to GOL+CEL or GOL alone; 97 (45 vs. 52) patients completed the study at w108. Clinical characteristics of the randomized patients are shown in Tab. 1. The mSASSS change after w108 was 1.1 (95%CI 0.2; 2.0) vs. 1.7 (95%CI 0.8; 2.6) in the GOL+CEL vs. GOL alone groups, respectively, p=0.79. Figure 1 shows the cumulative probability of the mSASSS change in both treatment arms. New syndesmophytes in the opinion of three readers occurred in 11% vs. 25% of the patients in the GOL+CEL vs. GOL alone groups, respectively, p=0.12. During the study, a total of 14 serious adverse events (SAE) were reported (7 in the GOL+CEL group, 5 in the GOL alone group and 2 during the run-in phase). Figure 1. Cumulative probability plot of mSASSS progression over 108 weeks of treatment. Conclusion In this study, a combined therapy with GOL+CEL did not show significant superiority over GOL monotherapy in retarding radiographic spinal progression over two years in r-axSpA patients. However, the observed numerical reduction in radiographic spinal progression associated with the combined treatment might be, however, clinically relevant for patients at high risk for progression. Table 1. Baseline characteristics of randomized patients Parameters GOL+CEL N=54 GOL alone N=55 All patients N=109 validn value validn value validn value Sex, male n (%) 54 40 (74.1) 55 41 (74.5) 109 81 (74.3) Age, years Mean (SD) 54 39.9 (9.9) 55 37.5 (10.8) 109 38.7 (10.4) Smoker n (%) 53 19 (35.8) 55 22 (40) 108 41 (38) HLA-B27 positivity n (%) 54 45 (83.3) 51 47 (92.2) 105 92 (87.6) BASDAI Mean (SD) 54 6.2 (1) 55 6.1 (1.1) 109 6.1 (1.1) BASMI Mean (SD) 54 2.6 (1.9) 54 2.9 (1.4) 108 2.8 (1.6) CRP 〉 5 mg/L n (%) 54 38 (70.4) 55 38 (69.1) 109 76 (69.7) ASDAS-CRP Mean (SD) 54 3.6 (0.6) 55 3.7 (0.9) 109 3.7 (0.8) Prior bDMARDs n (%) 54 17 (31.5) 55 9 (16.4) 109 26 (23.9) Presence of ≥ 1 syndesmophyte(s) n (%) 54 27 (50) 55 28 (50.9) 109 55 (50.5) mSASSS Mean (SD) 54 13.5 (16.9) 55 10.3 (13.2) 109 11.9 (15.2) Acknowledgements The CONSUL study has been supported by a grant from the German Ministry of Education and Research (BMBF), grant number FKZ 01KG1603 and study medication (golimumab) was provided free of charge by MSD Sharp & Dohme GmbH, Munich, Germany. Furthermore we would like to thank Anne Weber, Bianca Mandt, Claudia Lorenz, Hildrun Haibel, Judith Rademacher, Laura Spiller, Petra Tietz as well as all participating rheumatologist and included patients. Disclosure of Interests Fabian Proft Speakers bureau: AMGEN, AbbVie, BMS, Celgene, Janssen, MSD, Novartis, Pfizer, Roche, UCB, Consultant of: Novartis, Grant/research support from: Novartis, UCB, Lilly, Burkhard Muche Speakers bureau: UCB Pharma, AMGEN, Consultant of: UCB Pharma, AMGEN, Valeria Rios Rodriguez Speakers bureau: AbbVie, Falk e.V., Murat Torgutalp: None declared, Mikhail Protopopov Consultant of: Novartis, Joachim Listing: None declared, Maryna Verba: None declared, Uta Kiltz: None declared, Jan Brandt-Juergens: None declared, Maren Sieburg: None declared, Swen Holger Jacki: None declared, Joachim Sieper Speakers bureau: AbbVie, Janssen, Merck, Novartis, Consultant of: Abbvie, Janssen, Lilly, Merck, Novartis, UCB, Denis Poddubnyy Speakers bureau: AbbVie, Bristol-Myers Squibb, Eli Lilly, MSD, Novartis, Pfizer, and UCB, Consultant of: AbbVie, Biocad, Eli Lilly, Gilead, GlaxoSmithKline, Janssen, MSD, Novartis, Pfizer, Samsung Bioepis, and UCB, Grant/research support from: AbbVie, Eli Lilly, MSD, Novartis, and Pfizer.