In total, 519 patients were enrolled. Of these, 427 cases (82.3%) were female. The mean age was 32 (24-45) years, and the median disease course was 21(4.0-70.5) months. The most common manifestation was dizziness (41.4%), followed by fatigue (33.3%) and chest pain (22.2%). Pulselessness was observed in 41.8% of patients, vascular bruit in 44.5% cases, and both were more commonly observed in the active group. The most common imaging type was type V (35.1%), followed by type I (28.5%), type IV (10.2%), type IIb (7.7%), type IIa (7.1%), and type III (3.9%) (Table 1).
Comparisons of disease characteristics between active and inactive patients
According to Kerr criteria, 406 cases (72.2%) were defined as active disease. There was no significant difference between active and inactive groups in age, sex, disease course, and imaging types. Patients with active disease had higher frequency of fatigue, night sweat, chest pain, abdominal pain, pulselessness, and vascular bruit than patients with inactive disease (P < 0.05). The prednisone, cyclophosphamide, and methotrexate were the most commonly used drugs in TA patients, but there was no significant difference between two groups (Table 1).
Compared with those in inactive group, complements including C3 [1.00 (0.91 – 1.15) vs 1.19 (1.03 – 1.56), P < 0.001)], C4 [0.22(0.19 – 0.27) vs 0.25(0.20 – 0.30), P = 0.040)], and hemolytic complement (CH50, 59.3 ± 17.9 vs 66.4 ± 18.1, P = 0.015) were significantly higher in the active group. Moreover, serum levels of ESR, CRP, interleukin-6 (IL-6), platelets (PLT), globulin, immunoglobin A (IgA), and immunoglobin G (IgG) were also significantly higher in the active group compared with that in the inactive group (P < 0.05) (Table 1).
The relationships between complements and other biomarkers with disease activity
Then, logistic analysis was performed to clarify the relationships between different biomarkers with disease activity. In univariate regression analysis, it revealed that C3 and CH50, together with PLT, globulin, CRP, IgA, IgG, and IL-6 were positively correlated with disease activity (OR > 1, P < 0.05). However, in multivariate regression analysis, C3 levels [odds ratio [OR] (95%CI): 10.710(1.825 – 62.835), P = 0.009] and CRP [OR (95%CI): 1.041(1.009 – 1.073), P = 0.011] were independently associated with active disease. (Supplementary Table S1)
In the scatter plot, C3, C4, and CH50 increased with Kerr score significantly and C3 was significantly positively associated with ESR, CRP, and IL-6 (r > 0.4, P < 0.001) (Figure 1, Supplementary Figure S2-3). Furthermore, cluster analysis showed that patients could be clustered into two groups based on C3, CH50, PLT, globulin, CRP, IgA, IgG, IL-6, ESR, and Hb levels. The principal component analysis revealed that C3, CH50, CRP, IL-6, PLT, and ESR were assigned to the same major component consisting of inflammatory biomarkers (Figure 2). These data indicated that C3 levels were associated with the disease activity.
The value of C3 and other biomarkers in identifying disease activity for TA
In the diagnosis test, the C3 cut-off value for identifying active disease was 1.085 g/L, with the sensitivity of 69.9%, the specificity of 66.7%, and the AUC of 0.715(0.650 – 0.781). In comparison, the cut-off of CRP was 10.65 mg/L, with sensitivity of 50.7%, specificity of 82.4% and the AUC of 0.703(0.647 – 0.760). Moreover, the cut-off of ESR was 26.5 mm/H, with 63.8% sensitivity, 73.1% specificity and the AUC of 0.766(0.698 – 0.800). Further combined tests showed that combining CRP and C3 in parallel test, the sensitivity could be improved to 85.1%and the specificity was 55.0%. In serial test, the specificity was improved to 94.1%, with a sensitivity of 35.4%. (Table 2, Figure 1)
In addition, results of the NRI [OR (95%CI): 0.328(0.224 – 0.431), P < 0.001] and IDI [OR (95%CI): 0.389(0.312 – 0.466), P < 0.001] revealed that the introduction of C3 improved the ability of CRP to distinguish disease activity significantly.
The validation of the value of combination of CRP and C3 in distinguishing active disease
In the internal validation, the 10-fold cross-validation revealed that the accuracy of the training group was more than 75% in the parallel test of CRP and C3, among which the maximal accuracy was 90.9% in the training group with the corresponding accuracy of 83.7% in the test group (Supplementary Table S2).
In the external validation, 53 cases of independent TA patients were employed to further validate the universality of the results, among whom, 24 (55.8%) cases were in active status according to the Kerr criteria. There was no significant difference between patients from the original dataset and validation dataset in age, sex, and levels of ESR, CRP, and C3. The AUC of CRP and C3 was 0.721 and 0.692, with the accuracy of 72.0% and 67.3%, respectively in validation dataset. The AUC was 0.721 with the accuracy of 72.7% in the parallel test of CRP and C3, while the AUC of serial test of CRP and C3 was 0.721 with the accuracy of 70.4%. The scatter plot also showed that the introduction of C3 could reclassify some patients with CRP below the cut-off value as active disease (Figure 3, Supplementary Table S3 – 4).