This image depicts severe arteritis of the coronary artery with inflammation and thrombosis, with extension into the myocardium.
A proposed model to predict the risk of giant cell arteritis (GCA) prior to a temporal artery biopsy could help triage patients and guide decision making about the need for biopsy or monitoring (see Figure 1).
There’s no specific biomarker for GCA, and GCA can be a “diagnostic conundrum, especially when it presents in an occult or atypical fashion,” according to the researchers who published the development and validation data on their multivariable prediction model in a recent issue of Clinical Ophthalmology.1
Edsel Ing, MD, MPH, an ophthalmologist at Michael Garron Hospital and associate professor at the University of Toronto, and his colleagues note that even though several clinical prediction rules in the diagnosis and management of patients with suspected GCA exist, few were developed using more than 500 temporal artery biopsies or 100 biopsy-positive GCA cases, and few included external validation. The group’s research was compliant with the TRIPOD Initiative, a set of recommendations for reporting research that develops, validates or updates a prediction model so that bias risk and potential usefulness of the model can be adequately assessed.