Multivariable prediction model for suspected giant cell arteritis

Authors: Edsel Ing, Gabreiela Lahaie Luna, Andrew Toren, Royce Ing, John J. Chen, Nitika Arora, J. Alexander Fraser, Felix Tyndel, Arun Sundaram, Cindy Lam, Vivek Patel, Ezekiel Weis, Steven Gilberg, Christian Pagnoux, Martin ten Hove
Author Disclosure Block: E. Ing: None. G. Lahaie Luna: None. A. Toren: None. R. Ing: None. J.J. Chen: None. N. Arora: None. J. Fraser: None. F. Tyndel: None. A. Sundaram: None. C. Lam: None. V. Patel: None. E. Weis: None. S. Gilberg: None. C. Pagnoux: None. M. ten Hove: None.

Abstract Body:

Purpose: To develop and validate a diagnostic prediction model for patients with suspected giant cell arteritis (GCA).

Study Design: A retrospective review of consecutive adult patients undergoing temporal artery biopsy (TABx) for suspected GCA was conducted at seven university centers.

Methods: The pathologic diagnosis was considered the final diagnosis. The predictor variables were age, gender, new onset headache, clinical temporal artery abnormality, jaw claudication, ischemic vision loss (VL), diplopia, erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), and platelet level. Multiple imputation was performed for missing data. Logistic regression was used to compare our models with the non-histologic American College of Rheumatology GCA classification criteria (ACR). Internal validation was done with 10-fold cross validation and bootstrap. External validation was performed by geographic site.

Results: There were 530 complete TABx records; 397 were negative and 133 positive. Age, jaw claudication, VL, platelets and log CRP were statistically significant predictors for positive TABx, but ESR, gender, headache and temporal artery abnormality were not. The parsimonious model had a cross-validated bootstrap AUROC 0.810 (95%CI .766, .854), geographic external validation AUROC’s 0.75-0.85, calibration p H-L=.812, sensitivity 43.6% and specificity 95.2%, and outperformed the ACR criteria.  Online calculator: https://docs.google.com/spreadsheets/d/1wlRFGleW2Vf-LlylmY76KSTzIAf1TrX5U_1770HhD1Y/edit#gid=0

Conclusions: Our prediction rule with calculator and nomogram aids in the triage of patients with suspected GCA, and may decrease the need for TABx in select low score risk subjects. However, misclassification remains a concern.