ROC analysis was performed to measure the diagnostic value for IgAN of the 15 different serological parameters between the IgAN and non-IgAN groups. The area under the curves (AUCs) of TP (AUC = 0.78), TC (AUC = 0.73), FIB (AUC = 0.74), D2 (AUC = 0.71), IgA (AUC = 0.74), and IgG (AUC = 0.71) were more than 0.70 [Table 3].
Based on the PRE of the logistic regression analysis, the AUC of the “TC + FIB + D2 + IgA + age” combination was 0.86 (P < 0.001, 95% CI: 0.83–0.89), with a sensitivity and specificity of 85.98% and 73.85%, respectively [Figure 1].
We collected several representative clinical parameters to analyze the relationship between the pathological grades and laboratory test results. As shown in Table 5, the levels of UN and Cr were significantly higher in grade V than in grades II–V, respectively (all P < 0.05). And the levels of TP, DB, and IgA were significantly increased in grades II–V compared with grade I (all P < 0.05).
IgAN has a high incidence worldwide and a large proportion of IgAN patients will progress to ESRD. Therefore, it is of great value to evaluate the disease severity and development of IgAN. Currently, although several IgAN biomarkers have been extensively researched, none have been applied for its screening in clinical practice. Moreover, a number of computational studies have been performed on many types of kidney disease, but none have focused on noninvasively diagnosing IgAN. In the present study, we used retrospective data to analyze the serological parameters and pathological stages of patients with IgAN and to establish a noninvasive diagnostic model for IgAN.
Based on the statistical analyses and clinical experience, 15 out of 20 routine and useful parameters were selected as predictors of IgAN: TP, TB, DB, Cr, Ua, TC, TG, LDH, HDL, LDL, FIB, D2, IgA, IgG, and IgE [Table 2]. Compared with previous studies, this study included more characteristics, including fibrinogen, D-dimer, serum IgA, and C3, all of which are known biomarkers of kidney disease.[16,28] In addition, ROC analysis was performed to further assess the diagnostic value of the 15 parameters and the results showed that the AUCs of TP, TC, FIB, D2, IgA, and IgG were all more than 0.7 [Table 3]. Although serum IgA appears not to be a specific biomarker of IgAN, previous studies have reported that IgA levels are still statistically different and have differentially diagnostic value, especially when combined with other clinical parameters. Berthoux et al reported that IgG was a biomarker for the prediction of clinicopathologic recurrence events in IgAN. Our non-IgAN group consists mainly of membranous nephropathy, minimally pathological nephropathy, mesangial proliferative glomerulonephritis and other diseases characterized by nephrotic syndrome. Patients with nephrotic syndrome are often in a state of hypercoagulability, hyperfibrinolysis, hyperlipemia, and hypoproteinemia. This may explain why the relevant index levels for blood clotting and blood lipids were higher in the non-IgAN group than in the IgAN group, such as FIB, D2, and TC, while the TP levels were lower in the non-IgAN group than in the IgAN group.
The multivariate logistic regression analysis requires that each explanatory variable is independent. Based on our clinical experience, the level of TP is not independent of IgA and IgG levels. Therefore, we removed TP and selected the other 5 parameters for further analysis. Given that the incidence of IgAN varies from age to age, we added the age variable to the logistic regression model. The predicted probabilities were calculated based on logistic regression analysis [Table 4]. The AUC of the “TC + FIB + D2 + IgA + age” combination was 0.86, with a sensitivity of 85.98% and a specificity of 73.85% [Figure 1]. The established diagnostic model that combined multiple factors (TC, FIB, D2, IgA, and age) might be used for IgAN noninvasive diagnosis.
We found that the levels of UN and Cr were significantly higher in grade V patients than those in other grades. Furthermore, apparent increases in TP, DB, and IgA were observed in grades II–V compared with grade I [Table 5]. Many studies have shown that elevated Ua, serum Cr and other indicators are associated with an increased risk of IgAN.[33,34] However, there are limited reports on the relationship between these blood indicators and pathological grades or other indicators reflecting the severity of the disease.
Several strengths of our study should be stated. First, readily available clinical parameters such as patient demographics were applied. Second, all clinical characteristics were derived from biopsy-proven patients with IgAN. These patients were probably representative of patients with increased diagnostic uncertainty, which is the most challenging patients encountered in clinical practice. Lastly, our models were internally validated. However, this study has a few limitations that must be considered. First, this study was not a longitudinal investigation but rather a cross-sectional study. We are unable to determine the impact of these altered indicators on the pathogenesis of IgAN and whether this elevation is progressive or reversible. Second, because the study individuals were all of Chinese descent, we cannot ensure that our research results are applicable to individuals of other ethnic backgrounds. Third, this was a single-center study; further multicenter studies and large cohort studies should be conducted for validation.
This work was supported by grants from the National Key R&D Program of China (No. 2016YFC1305500), the National Natural Science Foundation of China (Nos. 61471399, 61671479, and 81670663), the National Key Research and Development Program (No. 2016YFC1305404), and the Joint Funds of National Natural Science Foundation of China and Henan Province (No. U1604284).
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