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Risk factors and predictive model for renal outcomes in autoimmune membranous nephropathy with and without acute
Zhenzhou Li1,2,3, Liyan Yang1,2,3, Linxia Wei1,2
1Department of Nephrology, Blood Purification Research Center, the First Affiliated Hospital, Fujian Medical University, Fuzhou, Fujian, China.
Objective:
This study aimed to delineate the risk factors affecting renal outcomes in autoimmune membranous nephropathy (aMN) with or without acute kidney injury (AKI) and develop a predictive model.
Methods:
This retrospective cohort study included 441 patients with biopsy-confirmed aMN from the First Affiliated Hospital of Fujian Medical University (January 2010 to March 2023). Patients were grouped based on the presence of AKI and followed up until a renal endpoint event (progression to end-stage renal disease, initiation of dialysis, or either a >40% decline in estimated glomerular filtration rate from baseline or a doubling of serum creatinine levels from baseline, both sustained for ≥3 months) or study endpoint (March 2024). Clinicopathological and renal outcomes were collected and analyzed. Risk factors for renal endpoints were identified via Cox regression analyses, and a nomogram was constructed. Model performance was evaluated using the C-index, time-dependent receiver operating characteristic (Time-ROC) curves, calibration curves, and decision curve analysis (DCA). Kaplan-Meier survival curves compared renal survival between AKI subgroups.
Results:
Among 441 patients, 109 (24.72%) experienced AKI. Renal endpoint events occurred in 40.4% of the AKI group and 4.5% of the non-AKI group. Multivariate Cox regression identified AKI (HR = 7.298, P < 0.001), triglycerides (HR = 1.140, P = 0.002), serum creatinine (HR = 1.008, P = 0.012), hematuria (HR = 2.246, P = 0.040), and kidney anti-M-type phospholipase A2 receptor staining 4+ (HR = 2.473, P = 0.003) as independent risk factors, while serum C3 (HR = 0.082, P < 0.001) was an independent protective factor. The nomogram had a C-index of 0.845 (P < 0.001), with Time-ROC AUCs of 0.92, 0.81, 0.83, and 0.87 for 3 to 6 years, respectively. Calibration plots revealed good consistency between the predicted and actual probabilities. DCA indicated that the nomogram had potential clinical utility. Kaplan-Meier analysis showed lower cumulative renal survival in patients with AKI (P < 0.001).
Conclusions:
The risk factor model suggests that renal outcomes in patients with aMN can be predicted. Early assessment and management targeting these identified risk factors could help delay renal function decline in these patients.
