Background Rheumatoid arthritis (RA) requires early diagnosis and tight surveillance of disease activity. Patient self-sampling of blood for the analysis of autoantibodies and inflammation markers could facilitate the identification of patients at-risk for RA and improve tight disease monitoring [1]. Objectives A randomized, controlled trial to evaluate the feasibility, acceptability and accuracy of an upper arm self-sampling device (UA) and finger prick-test (FP) to measure capillary blood from RA patients for C-reactive protein (CRP) levels and the presence of IgM rheumatoid factor (RF IgM) and anti-cyclic citrullinated protein antibodies (anti-CCP IgG). Methods 50 RA patients were randomly assigned in a 1:1 ratio to self-collection of capillary blood via UA or FP. Venous blood sampling (VBS) was performed as gold standard in both groups to assess the concordance of CRP levels as well as RF IgM and CCP IgG. General acceptability and pain during sampling were measured and compared between UA, FP and VBS. The number of attempts for successful sampling, requests for assistance, volume and duration of sample collection were also assessed. Results 49/50 (98%) patients were able to successfully collect capillary blood. Overall agreement between capillary and venous analyses for CRP (0.992), CCP IgG (0.984) and RF IgM (0.994) were good. In both groups 4/25 (16%) needed a second attempt and 8/25 (32%) in the UA and 7/25 (28%) in the FP group requested assistance. Mean pain scores for capillary self-sampling (1.7/10 ± 1.1 (UA) and 1.9/10 ± 1.9 (FP)) were lower on a numeric rating scale compared to venous blood collection (UA: 2.8/10 ± 1.7; FP: 2.1 ± 2.0). UA patients were more likely to promote the use of capillary blood sampling (net promoter score: +28% vs. -20% for FP) and were more willing to perform blood collection at home (60%) vs. 32% for FP). Conclusion This study shows that self-sampling is accurate, feasible and well accepted among patients. The implementation could allow tight remote monitoring of disease activity as well as identifying patients at-risk for RA and potentially other rheumatic diseases. References: [1]Knitza J, Knevel R, Raza K, Bruce T, Eimer E, Gehring I, et al. Toward Earlier Diagnosis Using Combined eHealth Tools in Rheumatology: The Joint Pain Assessment Scoring Tool (JPAST) Project. JMIR Mhealth Uhealth. 2020;8:e17507. Acknowledgements We thank all patients for their participation in this study. This study is part of the PhD thesis of the first author JK (AGEIS, Université Grenoble Alpes, Grenoble, France). We thank Josefine Born and Deniz Krämer for their help recruiting patients. Disclosure of Interests Johannes Knitza Grant/research support from: Thermo Fisher Scientific, Novartis, Koray Tascilar: None declared, Nicolas Vuillerme: None declared, Ekaterina Vogt Employee of: Thermo Fisher Scientific, Paul Matusewicz Employee of: Thermo Fisher Scientific, Giulia Corte: None declared, Louis Schuster: None declared, Timothée Aubourg: None declared, Gerlinde Bendzuck: None declared, Marianne Korinth: None declared, Corinna Elling-Audersch: None declared, Arnd Kleyer: None declared, Sebastian Boeltz: None declared, Axel Hueber: None declared, Gerhard Krönke: None declared, Georg Schett: None declared, David Simon: None declared