Background: The serum immunoglobulin A (IgA)/C3 ratio is considered to be an effective predictor of IgA nephropathy (IgAN). This study sought to explore the diagnostic value of the IgA/C3 ratio in IgAN among primary glomerular nephropathy patients in China.

Methods: We recruited 1095 biopsy-diagnosed primary glomerular nephropathy patients, including 757 IgAN patients and 338 non-IgAN patients. Patient demographics, serum immunological indices, and other clinical examinations were measured. IgAN cases were propensity score matched (PSM) to non-IgAN cases on the logit of the propensity score using nearest neighbor matching in a 1:1 fashion, with a caliper of 0.02 with no replacements, according to age, gender, BMI, proteinuria level, and estimated glomerular filtration rate (eGFR).

Results: We found that in both the full cohort and PSM cohort, the IgA/C3 ratio in the IgAN group was significantly higher than that of the non-IgAN group. The same results were also obtained with stratification by different levels of proteinuria and renal function. In the PSM cohort, there was no difference in IgA/C3 ratio in patients with IgAN between different proteinuria groups and different chronic kidney disease (CKD) groups. The area under the ROC curve (AUROC) of the IgA/C3 ratio in distinguishing IgAN among primary glomerular disease was 0.767 in the full cohort, and 0.734 in the PSM cohort. The highest AUROC of the IgA/C3 ratio was in the ≤1 g/d proteinuria group (0.801 in the full cohort, and 0.803 in the PSM cohort); however, there was no difference between all CKD groups. Meanwhile, the diagnostic accordance rate for the diagnosis of IgAN among all patients with an IgA/C3 ratio > 3.5304 was as high as 92.02% in the full cohort. IgAN was independently correlated with IgA/C3 ratio in the full cohort by multivariate logistic regression analysis.

Conclusions: The present study provides clear evidence that the IgA/C3 ratio is an effective predictor of IgA diagnosis, especially in patients with proteinuria ≤1 g/d. In order to study the effectiveness of this biomarker, and to determine a standardized cut-off value, additional multicenter large-scale studies are needed.

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