Distribution of arterial lesions in Takayasu's arteritis and giant cell arteritis

Abstract

Objectives To compare patterns of arteriographic lesions of the aorta and primary branches in patients with Takayasu’s arteritis (TAK) and giant cell arteritis (GCA). Methods Patients were selected from two North American cohorts of TAK and GCA. The frequency of arteriographic lesions was calculated for 15 large arteries. Cluster analysis was used to derive patterns of arterial disease in TAK versus GCA and in patients categorised by age at disease onset. Using latent class analysis, computer derived classification models based upon patterns of arterial disease were compared with traditional classification. Results Arteriographic lesions were identified in 145 patients with TAK and 62 patients with GCA. Cluster analysis demonstrated that arterial involvement was contiguous in the aorta and usually symmetric in paired branch vessels for TAK and GCA. There was significantly more left carotid (p=0.03) and mesenteric (p=0.02) artery disease in TAK and more left and right axillary (p<0.01) artery disease in GCA. Subclavian disease clustered asymmetrically in TAK and in patients ≤55 years at disease onset and clustered symmetrically in GCA and patients >55 years at disease onset. Computer derived classification models distinguished TAK from GCA in two subgroups, defining 26% and 18% of the study sample; however, 56% of patients were classified into a subgroup that did not strongly differentiate between TAK and GCA. Conclusions Strong similarities and subtle differences in the distribution of arterial disease were observed between TAK and GCA. These findings suggest that TAK and GCA may exist on a spectrum within the same disease.

Recent advances in Takayasu's arteritis

“…Cluster analysis revealed that TAK lesions mostly develop in a symmetric manner in paired vascular territories and disease extension is contiguous in the aorta (14). A similar finding was also observed in the case of GCA (15). Computer-derived classification models distinguished TAK from GCA in 2 subgroups, defining 26% and 18% of the study sample, respectively; however, 56% of patients were classified into a subgroup that did not strongly differentiate between TAK and GCA.…”

“…However, the limitations of physical examination were recently shown in a study comparing physical signs with imaging data (15). When bruits, absent pulses, or blood pressure differences are evaluated as physical signs, the presence of any single item has a sensitivity of 52%-71% and a specificity of 59%-86%.…”

Prevalence and Responsiveness to Treatment of Lung Abnormalities on Chest Computed Tomography in Patients With Microscopic Polyangiitis: A Multicenter, Longitudinal, Retrospective Study of One Hundred Fifty Consecutive Hospital‐Based Japanese Patients

“…To identify the clustering patterns of lung abnormalities on chest CT images, latent class analysis was performed. An optimal number of latent classes was determined using model fit statistics such as Bayesian information criterion (BIC) and consistent Akaike information criterion (CAIC) values (24,25). Latent class analysis was performed using SAS version 9.3 (SAS Institute) and PROC LCA (26), whereas other statistical analyses were performed using SPSS version 21.0 (IBM Japan).…”

Reassessing classification criteria for Takayasu arteritis: Comment on the article by Lee et al

“…As recent observations have shown that the histopathology of arterial lesions in these 2 diseases is difficult to distinguish, it is speculated whether TA and GCA are part of a spectrum of manifestations within a single disease (5). On angiography, arteriographic lesions are recognized as the sequelae of inflammation; strong similarities and subtle differences in these lesions were observed between GCA and TA (6).…”