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Performance of the modified 2022 ACR/EULAR giant cell arteritis classification criteria without age restriction for discriminating from Takayasu arteritis

Arthritis Research & Therapy volume 27, Article number: 19 (2025) Cite this article

Abstract

Objective

To evaluate the ability to discriminate giant cell arteritis (GCA) from Takayasu arteritis (TAK) according to the modified 2022 American College of Rheumatology/European Alliance of Associations for Rheumatology (ACR/EULAR) GCA classification criteria.

Methods

Patients enrolled in the Japanese nationwide retrospective registry were evaluated using the criteria with partial modification; wall thickening of descending thoracic-abdominal aorta were mainly diagnosed by contrast-enhanced computed tomography (CT) or magnetic resonance imaging instead of evaluating with positron emission tomography (PET)-CT. The discriminability of the criteria was evaluated using C-statistic (> 0.7: good ability).

Results

Newly diagnosed patients with GCA (n = 139) and TAK (n = 129) were assessed, and 23.3% of TAK were aged 50 years or older at onset. The sensitivity of the modified 2022 ACR/EULAR GCA classification criteria with a score ≥ 6 was 82.0%, 68.5%, and 32.1% in all GCA, GCA with large-vessel involvement, and GCA without cranial arteritis, respectively. The specificity of the modified criteria was 96.1% for the 129 TAK as controls. Five patients with late-onset TAK met the modified criteria, and four had cranial signs and symptoms, two had bilateral axillary artery involvement, and four had descending thoracic-abdominal aorta involvement. The discriminability of the criteria was good (C-statistic: 0.986, 95% confidence interval [CI]: 0.976–0.996) and remained good after excluding age (C-statistic: 0.927, 95% CI: 0.894–0.961). The discriminability of a set of large-vessel lesions (bilateral axillary artery and descending thoracic-abdominal aorta) and inflammatory markers was markedly decreased with poor C-statistic value (C-statistic: 0.598, 95% CI: 0.530–0.667). Discriminability was improved after adding polymyalgia rheumatica (PMR) (C-statistic: 0.757, 95% CI: 0.700–0.813) or age (C-statistic: 0.913, 95%CI: 0.874–0.951) to the set of large-vessel lesions. In GCA patients with a score ≤ 5, 52% had bilateral subclavian and/or axillary artery involvement.

Conclusion

The modified 2022 ACR/EULAR GCA classification criteria well performed in classifying GCA and TAK without PET-CT in routine clinical practice. A set of items included in the modified GCA classification criteria had good discriminative ability for GCA and TAK, even when age was excluded. However, age restriction or PMR was required to distinguish GCA without cranial lesions from TAK.

Backgrounds

Temporal artery biopsy is a test with high specificity for the diagnosis of GCA [1, 2]. However, diagnostic yield depends on timing after treatment initiation and correct sampling, and the diagnostic sensitivity of biopsy is 30–50% [3]. The 1990 ACR criteria for the classification of GCA consist of clinical features of temporal arteritis and a positive temporal artery biopsy [4]. Recent advances in imaging technology revealed that patients with GCA frequently have lesions in the aorta and its major branches, and some of these patients do not have temporal artery involvement [5].

Previous studies have evaluated the similarities and differences between Takayasu arteritis (TAK) and GCA [6,7,8]. A cluster analysis of the patients from the Diagnostic and Classification Criteria for Vasculitis (DCVAS) cohort and a combined North American cohort showed different patterns of vascular involvement between TAK and GCA [9]. This finding led to the development of the 2022 ACR/EULAR classification criteria for GCA [10].

The Japan Research Committee of the Ministry of Health, Labour, and Welfare for Intractable Vasculitis (JPVAS) performed a nationwide, multicenter, retrospective cohort study of patients with GCA and TAK [11,12,13]. The clinical features of Japanese patients newly diagnosed with GCA were similar to those of Western countries, and large-vessel lesions were detected in approximately half of the patients [11].

Since GCA and TAK share common clinical signs and symptoms related to large-vessel lesions, it is important to validate the ability to discriminate GCA from TAK according to the 2022 ACR/EULAR GCA classification criteria, especially in a country like Japan where TAK is more prevalent compared to Europe and the United States. In this study, we evaluated the sensitivity and specificity of the modified 2022 ACR/EULAR GCA classification criteria in the JPVAS GCA/TAK cohort. Since late-onset TAK is prevalent in Japan [14, 15], we evaluated the discriminative ability of the items, except age, in the modified 2022 ACR/EULAR GCA classification criteria. We also evaluated the clinical characteristics of GCA not meeting the modified 2022 ACR/EULAR GCA classification criteria.

Methods

JPVAS study group and GCA/TKA cohort

The JPVAS is a study group on vasculitis supported by the Ministry of Health, Labour and Welfare of Japan. The study group implemented a nationwide, multicenter, retrospective cohort study of newly-diagnosed patients with GCA or TAK at 23 participating institutions between 2007 and 2014 [11, 13]. All incident cases were enrolled in the JPVAS cohort. Patients were not involved in the design and conduct of this research. The Ministry of Health, Labour and Welfare of Japan diagnostic criteria for TAK [16] were adopted for patients with TAK in the JPVAS cohort, which permitted the enrollment of patients with early-stage TAK having multiple or diffuse lesions of wall thickening, even in the absence of stenosis and dilatation of large-vessel lesions as well as late-onset TAK with onset at age 50 years or older, which differ from the 2022 ACR/EULAR TAK classification criteria [17]. For the diagnosis of GCA and TAK, medical records were reviewed retrospectively by experts in vasculitis practice at JPVAS, and eligible patients were classified as GCA or TAK according to the judgment of experts at each institution specialized in vasculitis, and no classification criteria were used to differentiate between GCA and TAK in the present cohort. When the steering committee of this study reevaluated the diagnosis of the enrolled patients, there was a risk that the decision would be influenced by the 2022 ACR/EULAR classification criteria for GCA and TAK. Therefore, the diagnosis of experts in vasculitis affiliated with JPVAS was used as the gold standard for the diagnosis in this study. We collected patient information using the same case report form on systemic symptoms, clinical features associated with cranial arteritis, clinical features associated with large-vessel lesions, PMR, inflammatory markers, and large-vessel imaging. We also assessed the histopathological findings of the temporal artery in patients with GCA.

Assessments

Patients were assessed for the following findings. Cranial features included a new headache, abnormal examination of the temporal artery, scalp tenderness, sudden visual loss or abnormalities, jaw claudication, and a positive temporal artery biopsy.Musculoskeletal features included PMR and myalgia/arthralgia/arthritis. Inflammatory markers included ESR and CRP. Aortic regions evaluated by imaging study included the subclavian artery, axillary artery, carotid artery, vertebral artery, brachiocephalic artery, ascending aorta, aortic arch, descending thoracic aorta, abdominal aorta, renal artery, mesenteric artery, iliac artery, and femoral artery. These lesions were detected by enhanced computed tomography (CT)/CT angiography (CTA), enhanced magnetic resonance imaging (MRI)/magnetic resonance angiography (MRA), or ultrasonography. In the JPVAS cohort, CT/CTA, MRI/MRA, or ultrasonography were mainly used to assess large-vessel lesions of GCA and TAK. Imaging examinations of large-vessel lesions were performed in 135 of the 139 patients at diagnosis of GCA [11] and in all cases of TAK [13]. Japanese insurance covers positron emission tomography (PET) only for evaluating disease activity in confirmed cases with GCA or TAK, and 38 or 50 received PET-CT at the diagnosis of GCA [11] or TAK [13], respectively.

Scoring using the modified 2022 ACR/EULAR classification criteria for GCA

Table 1 shows the different assessments performed using the 2022 ACR/EULAR GCA classification criteria [10] and the modified 2022 ACR/EULAR GCA classification criteria in the present study. Patients with a halo sign on temporal artery ultrasound had a score of 5 points in the 2022 ACR/EULAR classification criteria for GCA, but we did not assess the presence of a halo sign because the present retrospective cohort was not constructed for the purpose of evaluating the 2022ACR/EULAR classification criteria and because temporal artery lesions were primarily evaluated by temporal artery biopsy in GCA patients diagnosed between 2007 and 2014.

Table 1 Assessments used in the 2022 ACR/EULAR GCA classification criteria and the modified version in this study
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Japanese health insurance covers positron emission tomography (PET) only for assessing disease activity in confirmed cases with GCA or TAK by CT, MRI, or ultrasonography. Therefore, we needed to modify the classification criteria. In the modified 2022 ACR/EULAR GCA classification criteria, we assessed the presence of wall thickening in the descending thoracic aorta-abdominal aorta (The involvement of both the descending thoracic aorta and the abdominal aorta) on enhanced CT, enhanced MRI, ultrasonography, or fluorodeoxyglucose (FDG)-PET-CT instead of FDG-PET activity throughout the aorta using the 2022 ACR/EULAR classification criteria for GCA; patients with this feature had a score of 2 points.

A score ≥ 6 points in total using the above scoring system denoted GCA based on the 2022 ACR/EULAR classification criteria.

Statistical analysis

For comparison of GCA and TAK or late-onset TAK, continuous variables were evaluated by using Student’s t-test or the Mann–Whitney U test and categorical variables were examined by using the chi-squared test and Fisher’s exact test. For comparison between the three groups, continuous variables were analyzed through a one-way analysis of variance and Tukey’s multiple tests. Categorical variables were evaluated by multiple tests using the Z-test.

To calculate C statistics, we used multivariable logistic regression analysis to evaluate associations between GCA and items of the classification criteria. The predicted probability that a set of classification criteria items of interest could accurately diagnose GCA was recorded for each patient by using the logistic model. Moreover, the area under the receiver operating characteristic curve was calculated, as a C-statistic value [18]. A value for the C-statistic > 0.7 indicates a reasonable or good discriminative ability. All analytical procedures were performed using IBM SPSS Version 26.0 (IBM Corp., Armonk, NY, USA). All reported p-values were two-tailed, and the level of significance was set to < 0.05.

Results

Comparison of clinical parameters included in the 2022 ACR/EULAR GCA classification criteria in patients with GCA and TAK

Newly diagnosed patients with GCA (n = 139) and TAK (n = 129) were assessed (Table 2). The proportions of patients with cranial signs and symptoms (new headaches, scalp tenderness, abnormal examination of the temporal artery, sudden visual abnormalities, and jaw claudication), PMR, and myalgia/arthralgia/arthritis were significantly higher in GCA versus TAK (Table 2). Of the 139 patients with clinically diagnosed GCA, temporal artery biopsy was conducted in 87 (62.6%), and 70 (50.4%) had positive pathological findings in the temporal artery biopsy. Of the 139 patients with GCA, any large-vessel involvement by imaging was detected in 52.5%. Bilateral axillary arteries were observed in 10 patients (7.2%); eight patients were diagnosed with PET-CT; one patient had wall thickening on CTA; and one patient had arterial stenosis on CTA. Descending thoracic to abdominal aortic lesions were observed in 33 patients (23.7%); 32 patients were diagnosed with wall thickening by CTA or MRA (CTA: n = 27; MRA: n = 15) and 22 of them also had FDG uptake confirmed by PET-CT; and one patient was diagnosed by PET-CT alone. The proportions of bilateral axillary artery involvement and lesions of descending thoracic aorta-abdominal aorta were similar in GCA and TAK (Table 2). The proportion of bilateral axillary artery involvement (13.7%) and lesions of descending thoracic aorta-abdominal aorta (45.2%) in large-vessel GCA (LV-GCA) was numerically higher than those in TAK (Supplementary Table S1). The increase in odds ratio (OR) for LV-GCA of bilateral axillary artery involvement (OR:2.40; 95% confidence interval [95%CI]: 0.90–6.39) and descending thoracic aorta-abdominal aorta (OR:1.71, 95%CI: 0.95–3.08) was not statistically significant but showed a higher trend compared to ORs of unilateral left or right subclavian artery lesions, ascending aorta, aortic arch, aortic involvement of ≥ two lesions (Supplementary Table S1).

Table 2 Comparison of clinical parameters included in the modified 2022 ACR/EULAR GCA classification criteria in patients with GCA and TAK
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Comparison of clinical parameters included in the modified 2022 ACR/EULAR GCA classification criteria in patients with LV-GCA and late-onset TAK

In the JPVAS cohort, 23.3% of TAK cases had a late onset at age 50 years and older, and a similar trend was observed when comparing LV-GCA to late-onset TAK. Cranial signs and symptoms, PMR, and bilateral subclavian and/or axillary artery involvement skewed towards LV-GCA rather than late-onset TAK. Whereas, ascending aorta were towards late-onset TAK. However, the incidences of axillary arteries and descending thoracic-abdominal aorta in late-onset TAK were similar to those of LV-GCA (Table 3).

Table 3 Comparison of clinical parameters included in the modified 2022 ACR/EULAR GCA classification criteria in patients with LV-GCA and late-onset (≥ 50 years) TAK
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Sensitivity and specificity of the modified 2022 ACR/EULAR classification criteria for GCA

Among the 139 patients clinically diagnosed as having GCA (GCA cohort), 114 (82.0%) satisfied the modified 2022 ACR/EULAR GCA classification criteria, and 109 (78.4%) met the 1990 ACR GCA classification criteria (Table 4). In the 129 patients clinically diagnosed as having TAK (TAK cohort), five late-onset patients met the modified 2022 ACR/EULAR GCA classification criteria. Four of the five late-onset TAK had cranial signs and symptoms (headache in one, visual disturbance in two, jaw claudication in two), two had bilateral axillary artery involvement, four had descending thoracic-abdominal aorta involvement, three had ascending aorta and aortic arch involvement, and three had bilateral subclavian artery involvement. Two late-onset TAK with bilateral axillary artery involvement had also ascending aorta and aortic arch involvement. PMR was not reported in the all five late-onset TAK. Overall, the modified 2022 ACR/EULAR GCA classification criteria exhibited a specificity of 96.1%, and the specificity decreased to 83.3% for the 30 patients with late-onset TAK.

Table 4 Sensitivity and specificity of the modified 2022 ACR/EULAR classification criteria for GCA in the JPVAS cohort
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Among the 111 patients in the GCA cohort with cranial arteritis, 105 (94.6%) met the modified 2022 ACR/EULAR GCA classification criteria, and 106 (98.1%) met the 1990 ACR GCA classification criteria. Among the 73 GCA patients with large-vessel lesions and 28 GCA patients who did not have cranial arteritis, 50 (68.5%) and nine (32.1%) met the modified 2022 ACR/EULAR GCA classification criteria, and 43 (58.9%) and three (9.7%) met the 1990 ACR GCA classification criteria, respectively (Table 4).

Discriminability of items adapted to the modified 2022 ACR/EULAR GCA classification criteria, excluding age

We calculated the C-statistic to evaluate the discriminative ability of a combination of clinical parameters. Firstly, we evaluated the discriminative ability of a set of all items adopted in the modified 2022 ACR/EULAR GCA classification criteria as Model 1. This set included age ≥ 50 years, a new headache, scalp tenderness, abnormal examination of the temporal artery, sudden visual abnormalities, jaw claudication, PMR, a positive temporal artery biopsy, bilateral axillary artery involvement, descending thoracic-abdominal aorta involvement, and ESR ≥ 50 mm/h or CRP ≥ 1 mg/dL; the C-statistic value was 0.986 (95% CI: 0.976–0.996) (Fig. 1A and B). Even after the exclusion of age from Model 1 (Model 2), the discriminative ability of the combination of clinical parameters (excluding age) was good (C-statistic: 0.927, 95% CI: 0.894–0.961) (Fig. 1A and C). The C-statistic value was still keeping good discriminative ability after excluding a positive temporal artery biopsy from Model 2 (i.e., C-statistic > 0.7) (Fig. 1A and D). Following the exclusion of imaging findings related to large-vessel lesions from Model 3 (Model 4), the discriminative ability of clinical criteria regarding cranial signs and symptoms remained good (Fig. 1A and E).

Fig. 1
figure 1

The discriminating ability for GCA and TAK of a combination of clinical parameters was evaluated by C-statistic. Gray highlighting indicates that the item is included in the model 1–7 (A). ESR of ≥ 50 mm/hr or CRP of ≥ 1.0 mg/dL was included in all models. Age at onset ≥ 50 years1, positive temporal artery biopsy2, cranial signs and symptoms (new headache, scalp tenderness, abnormal examination of the temporal artery, sudden visual abnormalities, and jaw claudication)3, PMR, descending thoracic-abdominal aorta involvement4, bilateral axillary artery involvement5, bilateral subclavian and/or axillary artery involvement6 were selected as clinical parameters. The ROC curve was drawn to calculate the area under the ROC curve as a C-statistic. The C statistic represents the ability to discriminate GCA from TAK in model 1 (B), model 2 (C), model 3 (D), model 4 (E), model 5 (F), model 6 (G), and model 7 (H). A value for the C-statistic greater than 0.7 indicates a reasonable and good ability to discriminate between patients with GCA and TAK. CI, confidence interval; ROC, receiver operating characteristic; TAK, Takayasu arteritis

Full size image

Discriminative ability of items of large-vessel lesions in the modified 2022 ACR/EULAR GCA classification criteria, excluding age

In the presence of cranial signs and symptoms, the differential diagnosis between GCA and TAK is straightforward. Therefore, we evaluated the discriminative ability of a set of items excluding both cranial signs and symptoms and PMR. Initially, we assessed the ability of a set of imaging findings (i.e., bilateral axillary artery involvement and descending thoracic-abdominal aorta involvement), and ESR ≥ 50 mm/h or CRP ≥ 1 mg/dL (Model 5); the C-statistic value was markedly reduced to 0.598 (95%CI: 0.530–0.667) (Fig. 1A and F). Following the addition of PMR to Model 5 (Model 6), the discriminating power was improved (C-statistic: 0.757: 95%CI: 0.700–0.813) (Fig. 1A and G), and it was good discriminative ability (i.e., C-statistic > 0.7). The addition of age to Model 5 (Model 7) also improved the discriminative ability (C-statistic: 0.913, 95%CI: 0.874–0.951) (Fig. 1A and H).

Clinical features of patients who failed to meet the modified 2022 ACR/EULAR GCA classification criteria

Table 5 shows the clinical features of 25 patients who failed to meet the modified 2022 ACR/EULAR GCA classification criteria (i.e., score ≤ 5). The proportions of cranial signs and symptoms and PMR were significantly lower in GCA patients with a score ≤ 5 than in GCA patients with a score ≥ 6; these proportions were similar to those recorded for TAK. Imaging findings revealed that 92.0% of the 25 patients with GCA with a score ≤ 5 had any large-vessel involvement. However, the proportion of bilateral axillary artery involvement was 0%, while the proportion of bilateral subclavian and/or axillary artery involvement was 52% in GCA patients with a score ≤ 5, which was the highest among the three groups (Table 5). The proportion of descending thoracic-abdominal aorta involvement in GCA patients with a score ≤ 5 was similar to that recorded in GCA patients with a score ≥ 6 and TAK.

Table 5 Clinical features of patients who failed to meet the modified 2022 ACR/EULAR classification criteria of GCA
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Discussion

In the modified version of the 2022 ACR/EULAR GCA classification criteria used in our cohort, examination using PET-CT was not mandatory for the evaluation of aortic lesions. We evaluated descending thoracic to abdominal aortic lesions mainly by the detection of wall thickening through contrast-enhanced CT or MRI. Notably, the modified 2022 ACR/EULAR GCA classification criteria showed similar sensitivity and specificity to those of the original 2022 ACR/EULAR GCA classification criteria [10]. The discriminability between GCA and TAK by C-statistic using a set of modified criteria, excluding age, was good. These suggested that the modified 2022 ACR/EULAR GCA classification criteria without age restriction well performed to classify GCA. However, the discriminative ability of the set consisting of large-vessel lesions (bilateral axillary artery and descending thoracic-abdominal aorta) and inflammatory markers, was markedly reduced, and the addition of PMR or age to the set of large-vessel lesions improved the discriminative ability.

The DCVAS cohort showed specificity of the 2022 ACR/EULAR GCA classification criteria for a control group that included various types of vasculitis, including TAK. In another validation study of the 2022 ACR/EULAR GCA classification criteria, GCA was compared with suspected GCA as a control [19,20,21,22]. It was expected that the similar clinical presentation of GCA and TAK [6, 7] would decrease specificity when only TAK was used as a control, but the modified 2022 ACR/EULAR GCA classification criteria showed high specificity even when only TAK was used as a control. In addition, the modified criteria were valuable for classifying GCA and TAK, even when age was excluded. The results also confirmed a significant increase in sensitivity for GCA without cranial artery lesions compared with the 1990 ACR classification criteria. This observation was similar to the results obtained from the DCVAS cohort [10].

In the 2022 ACR/EULAR GCA classification criteria, patients aged 50 years or older at onset who had an elevation of inflammatory markers and lesions of both bilateral axillary arteries and descending thoracic-abdominal aorta were classified as GCA [10]. In the JPVAS cohort, a set of items including bilateral axillary artery lesions, lesions in the thoracic descending aorta to the abdominal aorta, and CRP or ESR alone (Fig. 1F, model 5) exhibited poor discriminative ability for GCA and TAK. However, this discriminative power improved after the addition of PMR (Fig. 1G, model 6), suggesting the important role of PMR in discriminating between LV-GCA without cranial signs and symptoms and TAK. This is consistent with the Giant-Cell Arteritis Actemra (GiACTA) trial entry criteria [23], which classified PMR with large-vessel involvement (detected by imaging) as indicative of active GCA.

The present study suggested that the age of onset 50 years or older was crucial for the discrimination of LV-GCA without both cranial artery lesions and PMR (Fig. 1H, model 7). Therefore, the modified 2022 ACR/EULAR GCA classification criteria were considered useful for discriminating the LV-GCA without both cranial artery lesions and PMR and the TAK with an age of onset less than 50 years.

Late-onset TAK has been recognized in Japan [14], and age restriction was not included in the Japanese diagnostic criteria for TAK [16]. The incidences of bilateral axillary arteries and descending thoracic-abdominal aorta in late-onset TAK were similar to those of LV-GCA, and the specificity of the modified 2022 ACR/EULAR GCA classification criteria decreased for the late-onset TAK. Late-onset TAK meeting the modified GCA classification criteria had cranial signs or bilateral axillary artery involvement despite having unilateral left subclavian artery involvement or ascending aorta-aortic arch involvement, which is characteristic of TAK [9, 15, 24,25,26]. These suggest that it might be challenging to distinguish LV-GCA without PMR and late-onset TAK in a few patients with large-vessel vasculitis with age of onset older than 50 years.

Previous studies comparing PET-CT with CT or MRI indicated that aortic lesions can be diagnosed with CT [27] or MRI [28]. In the 2023 update of the EULAR recommendations, FDG-PET is recommended as the first imaging, but MRI or CT can be alternatively used for the diagnosis of extracranial arteries [29]. In the present study, the descending thoracic and abdominal aortic lesions were mainly diagnosed by CT or MRI, and PET-CT was conducted in 70% of the patients diagnosed by CT or MRI. The good performance of the modified classification criteria supports that MRI or CT can be an alternative to FDG-PET.

The present study revealed an increased proportion of bilateral subclavian and/or axillary involvement in LV-GCA compared with TAK (Supplementary Table S1) and late-onset TAK (Table 3). In previous studies, bilateral subclavian lesions were a key finding for the definition of LV-GCA [9, 30, 31], while unilateral subclavian lesions (especially left subclavian lesions) were more common than bilateral subclavian lesions in patients with TAK [9, 15, 24,25,26]. The prevalence of bilateral subclavian and/or axially artery lesions was higher than that of bilateral axillary artery lesions in the epidemiological study in Japan [26], and other cohorts [10, 20, 22]. Since ultrasonography for axially arteries was not routinely conducted at the time of recruitment (2007–2014) in Japan, we may have failed to detect the presence of bilateral axillary artery lesions in GCA patients with bilateral subclavian artery lesions.

The combination of temporal and axillary artery ultrasound and clinical findings is useful in the diagnosis of GCA, and the presence of wall thickening on ultrasound with typical clinical manifestations of GCA can be diagnosed without a temporal artery biopsy [32, 33]. In addition, temporal artery biopsy is less sensitive than temporal artery ultrasound with equal specificity [3, 29]. The main limitation of the present study is the lack of data on the ultrasound findings of the temporal or axillary arteries. The prevalence of temporal artery lesions detected by biopsy in the present study was similar to the DCVAS cohorts [9] but was lower than those detected by ultrasound in previous validation cohorts in European countries [19,20,21]. In the axillary arteries, performing ultrasonography in all cases might result in an increased detection rate of lesions [34, 35]. In the present study, 80% of the patients with bilateral axillary artery lesions in the JPVAS cohort were diagnosed by PET-CT, and the prevalence of bilateral axially artery lesions in the present study was similar to the DCVAS cohorts [9] but was lower than those detected by ultrasound in the previous validation cohorts in European countries [19,20,21]. The prevalence of descending thoracic to abdominal aortic lesions is similar to the DCVAS and previous validation cohorts. The sensitivity of the classification criteria was lower in this study than in previous validation cohorts [19,20,21], both for GCA overall and for GCA patients without temporal artery lesions, and sensitivity may be improved by performing temporal artery and axillary artery ultrasound in all patients.

The possible other limitations of this study are discussed below. Firstly, the selection of imaging modality was at the discretion of the attending physician in the retrospective JPVAS cohort, which may have affected the sensitivity and specificity of the tested criteria. Secondly, the cohort enrolled incident cases at participating institutions affiliated with JPVAS. Thus, although the results are generalizable for Japanese patients, ethnic differences may affect the sensitivity and specificity of the classification criteria. Thirdly, in our case report forms, we did not collect information on imaging findings for the celiac artery.

In conclusion, the modified 2022 ACR/EULAR GCA classification criteria exhibited good discriminative ability for GCA and TAK including late-onset TAK without PET-CT in routine clinical practice. However, age restriction or PMR was required to distinguish GCA with lesions of bilateral axillary arteries and descending thoracic-abdominal aorta from TAK. A prospective cohort study of patients with LV-GCA and late-onset TAK is warranted in the future, with protocols for evaluation by both temporal artery and axillary artery ultrasound.

Data availability

All of the data supporting the conclusions of this article are included within the article.

References

  1. Hellmich B, Agueda A, Monti S, Buttgereit F, de Boysson H, Brouwer E, et al. 2018 Update of the EULAR recommendations for the management of large vessel vasculitis. Ann Rheum Dis. 2020;79(1):19–30.

    Article  PubMed  Google Scholar 

  2. Maz M, Chung SA, Abril A, Langford CA, Gorelik M, Guyatt G, et al. 2021 American College of Rheumatology/Vasculitis Foundation Guideline for the Management of Giant Cell Arteritis and Takayasu Arteritis. Arthritis Rheumatol. 2021;73(8):1349–65.

    Article  PubMed  Google Scholar 

  3. Monti S, Agueda AF, Luqmani RA, Buttgereit F, Cid M, Dejaco C, et al. Systematic literature review informing the 2018 update of the EULAR recommendation for the management of large vessel vasculitis: focus on giant cell arteritis. RMD Open. 2019;5(2):e001003.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Hunder GG, Bloch DA, Michel BA, Stevens MB, Arend WP, Calabrese LH, et al. The American College of Rheumatology 1990 criteria for the classification of giant cell arteritis. Arthritis Rheum. 1990;33(8):1122–8.

    Article  CAS  PubMed  Google Scholar 

  5. Gribbons KB, Ponte C, Craven A, Robson JC, Suppiah R, Luqmani R, et al. Diagnostic assessment strategies and disease subsets in giant cell arteritis: data from an international observational cohort. Arthritis Rheumatol. 2020;72(4):667–76.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Grayson PC, Maksimowicz-McKinnon K, Clark TM, Tomasson G, Cuthbertson D, Carette S, et al. Distribution of arterial lesions in Takayasu’s arteritis and giant cell arteritis. Ann Rheum Dis. 2012;71(8):1329–34.

    Article  PubMed  Google Scholar 

  7. Maksimowicz-McKinnon K, Clark TM, Hoffman GS. Takayasu arteritis and giant cell arteritis: a spectrum within the same disease? Medicine (Baltimore). 2009;88(4):221–6.

    Article  PubMed  Google Scholar 

  8. Michailidou D, Rosenblum JS, Rimland CA, Marko J, Ahlman MA, Grayson PC. Clinical symptoms and associated vascular imaging findings in Takayasu’s arteritis compared to giant cell arteritis. Ann Rheum Dis. 2020;79(2):262–7.

    Article  CAS  PubMed  Google Scholar 

  9. Gribbons KB, Ponte C, Carette S, Craven A, Cuthbertson D, Hoffman GS, et al. Patterns of arterial disease in Takayasu Arteritis and Giant Cell Arteritis. Arthritis Care Res (Hoboken). 2020;72(11):1615–24.

    Article  PubMed  Google Scholar 

  10. Ponte C, Grayson PC, Robson JC, Suppiah R, Gribbons KB, Judge A, et al. 2022 American College of Rheumatology/EULAR Classification Criteria for Giant Cell Arteritis. Arthritis Rheumatol. 2022;74(12):1881–9.

    Article  CAS  PubMed  Google Scholar 

  11. Sugihara T, Hasegawa H, Uchida HA, Yoshifuji H, Watanabe Y, Amiya E, et al. Associated factors of poor treatment outcomes in patients with giant cell arteritis: clinical implication of large vessel lesions. Arthritis Res Ther. 2020;22(1):72.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Sugihara T, Uchida HA, Yoshifuji H, Maejima Y, Naniwa T, Katsumata Y, et al. Association between the patterns of large-vessel lesions and treatment outcomes in patients with large-vessel giant cell arteritis. Mod Rheumatol. 2023;33(6):1145–53.

    Article  PubMed  Google Scholar 

  13. Uchida HA, Nakaoka Y, Sugihara T, Yoshifuji H, Maejima Y, Watanabe Y, et al. Clinical characteristics and treatment outcomes of patients with newly diagnosed Takayasu arteritis in japan during the first 2 years of treatment- a nationwide retrospective cohort study. Circ J. 2024. online ahead of print.

  14. Watanabe Y, Miyata T, Tanemoto K. Current clinical features of new patients with Takayasu Arteritis observed from cross-country research in Japan: age and sex specificity. Circulation. 2015;132(18):1701–9.

    Article  PubMed  Google Scholar 

  15. Yoshifuji H, Nakaoka Y, Uchida HA, Sugihara T, Watanabe Y, Funakoshi S, et al. Organ damage and quality of life in Takayasu Arteritis - evidence from a national registry analysis. Circ J. 2024;88(3):285–94.

    Article  CAS  PubMed  Google Scholar 

  16. Isobe M, Amano K, Arimura Y, Ishizu A, Ito S, Kaname S, et al. JCS 2017 guideline on management of vasculitis syndrome- digest version. Circ J. 2020;84(2):299–359.

    Article  PubMed  Google Scholar 

  17. Grayson PC, Ponte C, Suppiah R, Robson JC, Gribbons KB, Judge A, et al. 2022 American College of Rheumatology/EULAR classification criteria for Takayasu arteritis. Ann Rheum Dis. 2022;81(12):1654–60.

    Article  PubMed  Google Scholar 

  18. Sugihara T, Ishizaki T, Hosoya T, Iga S, Yokoyama W, Hirano F, et al. Structural and functional outcomes of a therapeutic strategy targeting low disease activity in patients with elderly-onset rheumatoid arthritis: a prospective cohort study (CRANE). Rheumatology (Oxford). 2015;54(5):798–807.

    Article  CAS  PubMed  Google Scholar 

  19. Narvaez J, Estrada P, Vidal-Montal P, Nolla JM. Performance of the new 2022 ACR/EULAR classification criteria for giant cell arteritis in clinical practice in relation to its clinical phenotypes. Autoimmun Rev. 2023;22(10):103413.

    Article  CAS  PubMed  Google Scholar 

  20. Molina-Collada J, Castrejon I, Monjo I, Fernandez-Fernandez E, Torres Ortiz G, Alvaro-Gracia JM, et al. Performance of the 2022 ACR/EULAR giant cell arteritis classification criteria for diagnosis in patients with suspected giant cell arteritis in routine clinical care. RMD Open. 2023;9(2):e002970.

    Article  PubMed  PubMed Central  Google Scholar 

  21. van Nieuwland M, van Bon L, Vermeer M, Brouwer E, Alves C. External validation of the 2022 ACR/EULAR classification criteria in patients with suspected giant cell arteritis in a Dutch fast-track clinic. RMD Open. 2023;9(3):e003080.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Hemmig AK, Aschwanden M, Imfeld S, Berger CT, Daikeler T. A diagnostic performance study of the 2022 American College of Rheumatology/EULAR classification criteria for giant cell arteritis in a cohort of patients presenting with suspected giant cell arteritis. Arthritis Rheumatol. 2023;75(6):1075–7.

    Article  PubMed  Google Scholar 

  23. Stone JH, Tuckwell K, Dimonaco S, Klearman M, Aringer M, Blockmans D, et al. Trial of tocilizumab in giant-cell arteritis. N Engl J Med. 2017;377(4):317–28.

    Article  CAS  PubMed  Google Scholar 

  24. Mutoh T, Shirai T, Fujii H, Ishii T, Harigae H. Insufficient use of corticosteroids without immunosuppressants results in higher relapse rates in Takayasu Arteritis. J Rheumatol. 2020;47(2):255–63.

    Article  CAS  PubMed  Google Scholar 

  25. Gudbrandsson B, Molberg O, Garen T, Palm O. Prevalence, incidence, and disease characteristics of Takayasu arteritis by ethnic background: data from a large, population-based cohort resident in Southern Norway. Arthritis Care Res (Hoboken). 2017;69(2):278–85.

    Article  PubMed  Google Scholar 

  26. Konda N, Sakai R, Saeki K, Matsubara Y, Nakamura Y, Miyamae T, et al. Nationwide clinical and epidemiological study of large-vessel vasculitis in Japan in 2017. Mod Rheumatol. 2023;34(1):167–74.

    Article  PubMed  Google Scholar 

  27. de Boysson H, Dumont A, Liozon E, Lambert M, Boutemy J, Maigne G, et al. Giant-cell arteritis: concordance study between aortic CT angiography and FDG-PET/CT in detection of large-vessel involvement. Eur J Nucl Med Mol Imaging. 2017;44(13):2274–9.

    Article  PubMed  Google Scholar 

  28. Quinn KA, Ahlman MA, Malayeri AA, Marko J, Civelek AC, Rosenblum JS, et al. Comparison of magnetic resonance angiography and (18)F-fluorodeoxyglucose positron emission tomography in large-vessel vasculitis. Ann Rheum Dis. 2018;77(8):1165–71.

    Article  PubMed  Google Scholar 

  29. Dejaco C, Ramiro S, Bond M, Bosch P, Ponte C, Mackie SL, et al. EULAR recommendations for the use of imaging in large vessel vasculitis in clinical practice: 2023 update. Ann Rheum Dis. 2024;83(6):741–51.

    Article  CAS  PubMed  Google Scholar 

  30. Brack A, Martinez-Taboada V, Stanson A, Goronzy JJ, Weyand CM. Disease pattern in cranial and large-vessel giant cell arteritis. Arthritis Rheum. 1999;42(2):311–7.

    Article  CAS  PubMed  Google Scholar 

  31. Muratore F, Kermani TA, Crowson CS, Green AB, Salvarani C, Matteson EL, et al. Large-vessel giant cell arteritis: a cohort study. Rheumatology (Oxford). 2015;54(3):463–70.

    Article  PubMed  Google Scholar 

  32. Sebastian A, van der Geest KSM, Tomelleri A, Macchioni P, Klinowski G, Salvarani C, et al. Development of a diagnostic prediction model for giant cell arteritis by sequential application of Southend Giant Cell Arteritis Probability Score and ultrasonography: a prospective multicentre study. Lancet Rheumatol. 2024;6(5):e291–9.

    Article  CAS  PubMed  Google Scholar 

  33. Molina Collada J, Martinez-Barrio J, Serrano-Benavente B, Castrejon I, Caballero Motta LR, TrivesFolguera L, et al. Diagnostic value of ultrasound halo count and Halo Score in giant cell arteritis: a retrospective study from routine care. Ann Rheum Dis. 2022;81(9):e175.

    Article  PubMed  Google Scholar 

  34. Hop H, Mulder DJ, Sandovici M, Glaudemans A, van Roon AM, Slart R, et al. Diagnostic value of axillary artery ultrasound in patients with suspected giant cell arteritis. Rheumatology (Oxford). 2020;59(12):3676–84.

    Article  CAS  PubMed  Google Scholar 

  35. Bull Haaversen AC, Brekke LK, Kermani TA, Molberg O, Diamantopoulos AP. Extended ultrasound examination identifies more large vessel involvement in patients with giant cell arteritis. Rheumatology (Oxford). 2023;62(5):1887–94.

    Article  PubMed  Google Scholar 

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Acknowledgements

The authors would like to acknowledge all investigators in the Japan Research Committee of the Ministry of Health, Labour, and Welfare for Intractable Vasculitis (JPVAS). In addition to the authors, the following investigators and institutions participated in this study: The First Department of Internal Medicine, University of Occupational and Environmental Health (Yoshiya Tanaka); Division of Rheumatology, Department of Internal Medicine, Keio University School of Medicine (Tsutomu Takeuchi), Department of Respiratory Medicine, Allergy and Clinical Immunology, Nagoya City University Graduate School of Medical Sciences (Taio Naniwa), Division of Rheumatology and Allergy, Department of Internal Medicine, St. Marianna University School of Medicine (Hiroko Nagafuchi, Takahiro Okazaki); Division of Rheumatology, Endocrinology and Nephrology, Hokkaido University Graduate School of Medicine (Tetsuya Horita, Tatsuya Atsumi); Kichijoji Asahi Hospital (Yoshihiro Arimura); Sakakibara Heart Institute (Mitsuaki Isobe); Department of Cardiovascular Surgery, Kawasaki Medical School (Kazuo Tanemoto); Department of Internal Medicine 3, Hamamatsu University School of Medicine (Noriyoshi Ogawa); Department of Rheumatology, Shimane University Faculty of Medicine (Yohko Murakawa); Department of Allergy and Clinical Immunology, Chiba University Hospital (Shunsuke Furuta); Department of Hematology, Clinical Immunology and Infectious Diseases, Ehime University Graduate School of Medicine (Hitoshi Hasegawa); Department of Rheumatology, School of Medicine, Tokyo Women's Medical University (Yasuhiro Katsumata); Department of Cardiovascular Medicine, University of Tokyo Graduate School of Medicine (Eisuke Amiya, Hiroshi Akazawa, Issei Komuro); Department of Rheumatology and Clinical Immunology, Saitama Medical Center, Saitama Medical University (Koichi Amano); Department of Immunology and Rheumatology, Clinical Neuroscience and Neurology, Endocrinology and Metabolism, Nagasaki University Graduate School of Biomedical Sciences (Atsushi Kawakami); Department of Internal Medicine, Juntendo University Koshigaya Hospital (Shigeto Kobayashi); Division of Nephrology, Department of Laboratory Medicine, Institute of Medical, Pharmaceutical and Health Sciences, Faculty of Medicine, Kanazawa University (Takashi Wada); Department of Nephrology and Dialysis, Kitano Hospital, Tazuke Kofukai Medical Research Institute (Eri Muso); Department of Hematology, Oncology, Nephrology, and Rheumatology, Akita University School of Medicine (Atsushi Komatsuda); Niigata Rheumatic Center (Satoshi Ito); Niigata Prefectural Shibata Hospital (Noriyuki Homma); Division of Clinical Immunology, Graduate School of Comprehensive Human Sciences, University of Tsukuba (Taichi Hayashi); Kurobe City Hospital (Shinichi Takeda): Division of Nephrology, Department of Laboratory Medicine, Institute of Medical, Pharmaceutical, and Health Sciences, Faculty of Medicine, Kanazawa University (Takashi Wada).

Funding

This work was supported by grants from the Ministry of Health, Labour and Welfare, Japan (H29-nanchitou (nan)-ippan-018, 20FC1044, and 23FC1019), the Japan Agency for Medical Research and Development (AMED) (JP17ek0109121 and 24ek0109633h0002), and the Ministry of Education, Culture, Sports, Science and Technology (23K09729).

Author information

Authors and Affiliations

  1. Department of Rheumatology, Graduate School of Medical and Dental Sciences, Institute of Science Tokyo, Tokyo, Japan

    Takahiko Sugihara

  2. Division of Rheumatology, Department of Internal Medicine, Toho University School of Medicine, 6-11-1 Omori-Nishi, Ota-Ku, Tokyo, 143-8541, Japan

    Takahiko Sugihara

  3. Division of Rheumatology, Department of Internal Medicine, Tokyo Women’s Medical University School of Medicine, Tokyo, Japan

    Masayoshi Harigai

  4. Department of Chronic Kidney Disease and Cardiovascular Disease, Dentistry and Pharmaceutical Sciences, Okayama University Graduate School of Medicine, Okayama, Japan

    Haruhito A. Uchida

  5. Department of Rheumatology and Clinical Immunology, Graduate School of Medicine, Kyoto University, Kyoto, Japan

    Hajime Yoshifuji

  6. Department of Cardiovascular Medicine, Graduate School of Medical and Dental Sciences, Institute of Science Tokyo, Tokyo, Japan

    Yasuhiro Maejima

  7. Department of Hematology, Clinical Immunology and Infectious Diseases, Ehime University Graduate School of Medicine, Ehime, Japan

    Jun Ishizaki

  8. Department of General Medicine, Kawasaki Medical School, Kurashiki, Japan

    Yoshiko Watanabe

  9. Division of Hematology, Rheumatology and Respiratory Medicine, Department of Internal Medicine, Faculty of Medicine, Kagawa University, Kagawa, Japan

    Hiroaki Dobashi

  10. Department of Nephrology and Rheumatology, Kyorin University School of Medicine, Tokyo, Japan

    Yoshinori Komagata

  11. Department of Internal Medicine and Rheumatology, Juntendo University School of Medicine, Tokyo, Japan

    Naoto Tamura

  12. Department of Vascular Physiology, National Cerebral and Cardiovascular Center Research Institute, Suita, Japan

    Yoshikazu Nakaoka

  13. Department of Cardiovascular Medicine, National Cerebral and Cardiovascular Center Hospital, Suita, Japan

    Yoshikazu Nakaoka

  14. Department of Cardiovascular Medicine, Osaka University Graduate School of Medicine, Suita, Japan

    Yoshikazu Nakaoka

Authors
  1. Takahiko Sugihara
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  2. Masayoshi Harigai
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  3. Haruhito A. Uchida
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  4. Hajime Yoshifuji
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  5. Yasuhiro Maejima
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  6. Jun Ishizaki
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  7. Yoshiko Watanabe
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  8. Hiroaki Dobashi
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  9. Yoshinori Komagata
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  10. Naoto Tamura
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  11. Yoshikazu Nakaoka
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Consortia

Japan Research Committee of the Ministry of Health, Labour, and Welfare for Intractable Vasculitis (JPVAS)

  • Yoshiya Tanaka
  • , Tsutomu Takeuchi
  • , Taio Naniwa
  • , Hiroko Nagafuchi
  • , Takahiro Okazaki
  • , Tetsuya Horita
  • , Tatsuya Atsumi
  • , Yoshihiro Arimura
  • , Mitsuaki Isobe
  • , Kazuo Tanemoto
  • , Noriyoshi Ogawa
  • , Yohko Murakawa
  • , Shunsuke Furuta
  • , Hitoshi Hasegawa
  • , Yasuhiro Katsumata
  • , Eisuke Amiya
  • , Hiroshi Akazawa
  • , Issei Komuro
  • , Koichi Amano
  • , Atsushi Kawakami
  • , Shigeto Kobayashi
  • , Takashi Wada
  • , Eri Muso
  • , Atsushi Komatsuda
  • , Satoshi Ito
  • , Noriyuki Homma
  • , Taichi Hayashi
  • , Shinichi Takeda
  •  & Takashi Wada

Contributions

TS and MH were responsible for conception and design, data collection, statistical analysis, critical revision, and manuscript writing. HAU and HY were responsible for conception and design, data collection, analysis, and critical revision. YN was responsible for conception and design, data collection, and critical revision. YM, JI, YW, HD, and YK were responsible for data collection. NT was responsible for conception and design, analysis, and critical revision. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Takahiko Sugihara.

Ethics declarations

Ethics approval and consent to participate

This study was conducted following the Declaration of Helsinki and the Ethical Guidelines for Epidemiological Research in Japan. The institutional review board of Tokyo Medical and Dental University as the main center (approval number: M2000-2084-01) and the additional 23 institutions approved our retrospective study without personally identifiable information. Patients received posters informing the present study, or the posters were displayed in the outpatient clinic of each facility.

Consent for publication

Not applicable.

Competing interests

TS has received research grants from AsahiKASEI Co., Ltd., Daiichi Sankyo., Chugai Pharmaceutical Co., Ltd., and Ono Pharmaceutical. TS has received speaker’s fee from Abbvie Japan Co., Ltd., AsahiKASEI Co., Ltd., Astellas Pharma Inc., Ayumi Pharmaceutical, Bristol Myers Squibb K.K., Chugai Pharmaceutical Co., Ltd., Eli Lilly Japan K.K., Mitsubishi-Tanabe Pharma Co., Ono Pharmaceutical, Pfizer Japan Inc., and Taisho Pharmaceutical Co., Ltd.. MH has received research grants from Boehringer-Ingelheim Japan, Inc., Bristol Myers Squibb Co., Ltd., Chugai Pharmaceutical Co., Mitsubishi Tanabe Pharma Co., Pfizer Japan Inc., Teijin Pharma Ltd. MH has received speaker’s fee from Boehringer-Ingelheim Japan, Inc., Bristol Myers Squibb Co., Ltd., Chugai Pharmaceutical Co., Ltd., Kissei Pharmaceutical Co., Ltd., Mitsubishi Tanabe Pharma Co., Ono Pharmaceutical Co., Ltd., Pfizer Japan Inc., and Teijin Pharma Ltd. MH is a consultant for Boehringer-Ingelheim, Bristol Myers Squibb Co., Kissei Pharmaceutical Co., Ltd. and Teijin Pharma. HAU belongs to the Department of Chronic Kidney Disease and Cardiovascular Disease which is endowed by Olba Healthcare Holdings, Boehringer Ingelheim, and Terumo Corporation. HY has received lecture fees from Chugai Pharmaceutical and consulting fees from Janssen. HD has received speaking fees, and/or honoraria from Abbvie, Asahi Kasei Pharma, Astellas, UCB Pharmaceutical, Ayumi Pharmaceutical, GlaxoSmithKline, Novartis Pharma, Eli Lilly Japan, and AstraZeneca. YK has received speaker’s fee from GlaxoSmithKline. NT has received research grants from Asahi Kasei Pharma, Asahi Kasei Medical, Ayumi, AbbVie, Eisai, Nippon Boehringer Ingelheim, Taisho, Tanabe Mitsubishi, Chugai. NT has received speaker’s fee and/or consulting fee from Asahi Kasei Pharma, AstraZeneca, AbbVie, Eli Lilly Japan, GlaxoSmithKline, Chugai, Novartis, Bristol Myers Squibb, Janssen. YN has received consulting fees from AbbVie, Janssen Pharmaceutical KK, and Chugai, and has received lecture fees from AbbVie and Chugai. YM, JI and YW has nothing to declare.

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Sugihara, T., Harigai, M., Uchida, H.A. et al. Performance of the modified 2022 ACR/EULAR giant cell arteritis classification criteria without age restriction for discriminating from Takayasu arteritis. Arthritis Res Ther 27, 19 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s13075-025-03486-y

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Keywords

Arthritis Research & Therapy

ISSN: 1478-6362

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