Background:Diagnosing patients with giant cell arteritis (GCA) remains difficult. Due to its non-specific symptoms, it is challenging to identify GCA in patients presenting with polymyalgia rheumatica (PMR), which is a more common disease (1). In addition, commonly used acute-phase markers fail to discriminate between GCA patients and (infectious) mimicry patients.Objectives:To investigate a selection of biomarkers for their utility in the accurate diagnosis of GCA in two cohorts.Methods:Treatment-naïve GCA patients participated in the Aarhus GCA/PMR cohort (N=52) and the Groningen GPS cohort (N=48). Symptoms and biomarker levels were compared to patients presenting phenotypically as isolated PMR, disease controls and healthy controls (HCs). Diagnosis or exclusion of diagnosis of GCA was based on clinical assessment and in the majority of cases aided by imaging. Serum/plasma levels of 12 biomarkers were measured by ELISA or Luminex.Results:In both the Aarhus and the GPS cohort, we found that weight loss, elevated erythrocyte sedimentation rate (ESR) and higher angiopoietin-2/-1 ratios but lower matrix metalloproteinase (MMP)-3 levels identify concomitant GCA in PMR patients (Figure 1). In addition, we confirmed (1) that elevated platelet counts are characteristic of GCA but not of GCA look-alikes, and that low MMP-3 and proteinase 3 (PR3) levels may help to discriminate GCA from other diseases (Figure 1). Multiple biomarkers of inflammation were found elevated in patient and disease control groups when compared to HCs.Conclusion:This study, performed in two independent cohorts, consistently shows the potential of angiopoietin-2/-1 ratios and MMP-3 levels to identify GCA in patients presenting with PMR. These biomarkers may be used to select which PMR patients require further diagnostic workup. Platelet counts may be used to discriminate GCA from GCA look-alike patients.Figure 1.Summary of the most important and consistent findings in both cohorts. A shows the four factors that perform best in discriminating GCA/PMR patients overlap from isolated PMR patients in both cohorts. B shows the four factors that perform best in discriminate GCA patients from GCA look-alike patients in both cohorts. Cut-off values for the biomarkers are calculated by the Youden index.References:[1]van der Geest, KSM, Sandovici M, Brouwer E, Mackie SL. Diagnostic accuracy of symptoms, physical signs, and laboratory tests for giant cell arteritis: A systematic review and meta-analysis. JAMA internal medicine. 2020.Disclosure of Interests:Yannick van Sleen: None declared, Philip Therkildsen: None declared, Annemieke Boots: None declared, Berit Dalsgaard NIelsen: None declared, Kornelis van der Geest: None declared, Peter Heeringa: None declared, Minke G. Huitema: None declared, M.D. Posthumus: None declared, Maria Sandovici: None declared, Erik Toonen Employee of: Is an employee of Hycult Biotech, Jannik Zijlstra: None declared, Ellen-Margrethe Hauge: None declared, Elisabeth Brouwer: None declared