Utility of Giant Cell Arteritis Risk Prediction Models

Authors: Hamza Inayat, Saerom Youn, Lulu Bursztyn. Western University.

Author Disclosures: Hamza Inayat: None Saerom Youn: None Lulu Bursztyn: None


Abstract Body: 

Purpose: Temporal artery biopsy (TAB) is the gold standard for diagnosis of giant cell arteritis (GCA), but is invasive, may miss pathological findings and is performed by a limited number of health care providers. The Edsel Ing GCA Risk Calculator, González‐López GCA Risk Calculator and Weis Prediction Model are tools that can be used to estimate a patient’s likelihood of GCA. The purpose of the current study was to investigate the utility of these prediction models to
triage which patients would most benefit from TAB. 

Study Design: A retrospective study of all patients who underwent a TAB by a single neuro‐ophthalmologist in London, ON, Canada over a 5‐year period. 

Methods: Data collected through open chart review included age, sex, GCA symptoms, C‐reactive protein, erythrocyte sedimentation rate, and platelets. Required values were entered into the different prediction models to evaluate the risk of GCA, and then compared to the TAB result and clinical diagnosis. Cut‐off values for 100% sensitivity and specificity for TAB result were used to determine if any TAB could be avoided where there was pre‐operative certainty of the result. 

Results: Among 155 eligible patients, the mean age was 73 years (SD=9 years) and 78.1% were female. TAB was negative for GCA in 100 patients (64.5%), positive in 42 patients (27.1%), showed isolated angiitis of the vasa vasorum in 10 patients (6.5%) and uncertain in 3 patients (1.9%). Of the patients with negative TAB, 21 were clinically determined to have GCA (13.5%). Using the Edsel Ing GCA Risk Calculator, there were no positive biopsies below the threshold of 10.59%, and no negative biopsies above 68.44%. Using the González‐López GCA Risk Calculator, there were no positive biopsies below the threshold of 0.27%, and no negative biopsies above the threshold of 98.08%. For the Weis prediction model, there were no positive biopsies with a score of less than 0.

Conclusions: Based on these cut‐off values, 41 biopsies (28.9%) could have been avoided using the Edsel Ing Calculator, 9 biopsies (6.34%) using the González‐López Calculator, and 28 (19.7%) using the Weis Prediction Model. The findings of the study suggests that the Edsel Ing GCA Risk calculator and the Weis Prediction Model are useful screening tools for GCA with the potential to improve the effective use of health care resources.

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