Objectives: To prevent complications of giant cell arteritis (GCA), early and accurate diagnosis is essential. Recently, Laskou et al. (2019) developed the giant cell arteritis probability score (GCAPS) which allows physicians to assess the likelihood of GCA at an early stage. The aim of this study was to validate the GCAPS in a Dutch hospital.
Methods: A retrospective cohort of patients with suspected GCA between January 1st, 2017 and October 1st, 2019 was used. As the variable extracranial artery abnormality was not measured, a modified GCAPS was used (m-GCAPS). Clinical diagnosis of the rheumatologist after six months follow-up was used as reference. The m-GCAPS was assessed for discrimination and calibration. We applied risk stratification according to Sebastian et al. (2020) (low, intermediate and high-risk groups based on the median and 75th percentile).
Results: Our study included 209 suspected GCA patients. 135 patients had complete records. Of these patients, 40 had GCA. The m-GCAPS had an area under the curve of 0.83, a sensitivity of 80.0% and specificity of 75.8% at the optimal cut-off value >10.5. The Hosmer-Lemeshow test was non-significant. Using risk stratification, GCA prevalence was 12.5% in the low (score<9), 23.3% in the intermediate (9-12) and 78.6% in the high-risk group (>12).
Conclusions: The m-GCAPS showed good discrimination and calibration in a Dutch retrospective cohort and can aid early recognition of GCA. Stratification into low, intermediate and high-risk is promising, but might need optimisation.