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Diagnostic Algorithm for Patients With Suspected Giant Cell Arteritis

Background: To identify clinical and laboratory factors contributing to the diagnosis of giant cell arteritis (GCA) and develop a diagnostic algorithm for the evaluation of GCA. Methods: Retrospective review of 213 consecutive cases of temporal artery biopsy (TAB) seen at a single academic center over a 10-year period (2000–2009). Pathologic specimens were re-reviewed and agreement between the original and second readings was assessed. A composite clinical suspicion score was created by adding 1 point for each of the following criteria: anterior extracranial circulation ischemia, new onset headache, abnormal laboratory results (erythrocyte sedimentation rate, C-reactive protein (CRP), or platelet count), jaw claudication, abnormal or tender superficial temporal artery, constitutional symptoms, and polymyalgia rheumatica; one point was subtracted if a comorbid condition could explain a criterion. Results: Of the 204 TABs analyzed, pathologic findings were confirmatory in 49 (24.0%) and suggestive in 12 (5.9%). TAB-positive patients were more likely to be older (age 75.2 ± 7.8 vs 69.7 ± 11.0 years, P = 0.0002), complain of jaw claudication (relative-risk = 3.26, P = 0.0014), and have thrombocytosis (relative–risk = 3.3, P = 0.0072) and elevated CRP (relative-risk = 1.8, P = 0.037). None of the patients with a clinical score less than 2 had a positive TAB. Diabetes mellitus and kidney disease were often the explanation for the symptoms and abnormal clinical finding(s) that led to a negative TAB. Conclusions: We propose a clinical algorithm that is highly predictive for a positive TAB and can be valuable in the evaluation process of suspected cases of GCA.