POS0934 VALIDATION OF THE GIANT CELL ARTERITIS PROBABILITY SCORE AT A LARGE TERTIARY CENTRE
Authors: Z. Yang, K. Bechman, D. Nagra, B. Zuckerman, M. Russell, E. Alveyn, I. Karafotias, M. A. Adas, A. Mahto, C. Wincup, H. K. Molabanti, H. Obaid, K. Pillai, J. Galloway
Journal: Annals of the Rheumatic Diseases (2024)

<h3>Background:</h3> Giant cell arteritis (GCA) is a large vessel vasculitis with a predominance affecting elderly Caucasian patients and is a medical emergency requiring prompt diagnosis and intervention. The GCA probability score (GCAPS) is a clinical tool developed to assist GCA assessment in the early stage of disease utilised in fast-track clinics. <h3>Objectives:</h3> To evaluate the validity of the GCAPS, and the sensitivity and specificity of the different GCAPS cut-off points in large tertiary centre with a high utilization of temporal artery US. <h3>Methods:</h3> This single-centred retrospective study was conducted from 2018 to 2023. Data from patients referred for a temporal artery ultrasound were collected. Clinical data were extracted from the secondary care record. GCAPS scores were calculated and patients were allocated a risk group [low risk &lt;9 intermediate risk: 9-12 and high risk&gt;12]. Patient characteristics were compared between groups using Chi-squared test and t-test where appropriate. Patients with ineligible or insufficient data were excluded from analyses. The performance of GCAPS in predicting a positive US or temporal artery positive diagnosis for GCA was assessed by receiver operating characteristic (ROC) analyses, and Area under the curve (AUC) under receiver operating characteristic (ROC) curve, sensitivity, specificity and accuracy of different GCAPS binary cut-off values were calculated. Multivariable logistic regression was used to test the associations between individual GCAPS components and US or temporal artery positive diagnosis. <h3>Results:</h3> There are 256 patients referred for temporal artery US of which 40 (16%) had confirmed GCA on either US or TAB. Of the cohort, 81 were in low risk, 108 in median risk and 57 in high risk, with a mean value of the GCAPS was 10.2 (3.2). The mean GCAPS of the group without confirmed GCA was 9.8 (3.1), compared with 12.5 (3.0) in the group with GCA (p&lt;0.001). In the confirmed GCA group, the distribution of GCAPS risk groups was shifted to the higher score (3.7% low risk, 15% medium risk, 34% high risk). The area under the ROC curve was 0.73 (95% CI 0.65–0.82). At the defined cut-off for intermediate risk (score &gt;=9) the GCAPS provided a sensitivity of 92% and specificity of 38%. At the cut-off for high risk (score &gt;=13), the GCAPS provided a sensitivity of 50% and specificity of 82%. In multivariable logistic regression analyses, increasing age group [OR 1.12 (95% CI 1.05-1.2); <i>P</i> &lt; 0.01], increasing CRP [OR 1.02 (95% CI 1-1.03); <i>P</i> &lt; 0.01], and the presence of Ischemic symptoms [OR 8.85 (95% CI 2.48-36.73); <i>P</i> &lt; 0.01] are more likely to lead a GCA diagnosis. <h3>Conclusion:</h3> The GCAPS performed well at identifying patients with confirmed GCA, and we would recommend its use. Increasing age, CRP and Ischemic symptoms were strong predictors of GCA, and a high clinical suspicion is always warranted in these individuals.REFERENCES: NIL. <b>Table 1.</b> Baseline table <h3>Acknowledgements:</h3> <b>NIL.</b> <h3>Disclosure of Interests:</h3> Zijing Yang: None declared, Katie Bechman UCB and viforpharma, Deepak Nagra: None declared, Benjamin Zuckerman: None declared, Mark Russell Lilly, Menarini, Galapagos, Edward Alveyn: None declared, Ioasaf Karafotias: None declared, Maryam A. Adas: None declared, Arti Mahto: None declared, Chris Wincup: None declared, Hemanth Kumar Molabanti: None declared, Hassan obaid: None declared, kavya pillai: None declared, James Galloway AbbVie, Biovitrum, BMS, Celgene, Chugai, Galapagos, Gilead, Janssen, Lilly, Novartis, Pfizer, Roche, Sanofi, Sobi and UCB, AbbVie, Biovitrum, BMS, Celgene, Chugai, Galapagos, Gilead, Janssen, Lilly, Novartis, Pfizer, Roche, Sanofi, Sobi and UCB.