Estimated Glomerular Filtration Rate Slope Predicts Survival and Renal Outcomes in Myeloperoxidase-Antineutrophil Cytoplasmic Antibody-Associated Glomerulonephritis: Development and Validation of a Pathogen-Free Model

Introduction: This study explores the potential of estimated glomerular filtration rate (eGFR) slope as a noninvasive marker for predicting renal survival and patient survival in myeloperoxidase (MPO)-antineutrophil cytoplasmic antibody-associated glomerulonephritis (AAGN). Methods: A total of 377 MPO-AAGN patients were included. Kaplan-Meier and Cox regression analyses were performed to assess the predictive value of eGFR slopes for renal survival and patient survival. Then, the models were validated by discrimination, calibration, and decision curve analysis. Results: The eGFR slope (calculated using a linear mixed-effects model with baseline and follow-up eGFR values up to defined timepoints), higher with better renal recovery, had a median of 2.54 (IQR: 0.49–6.02) mL/min/1.73 m2/month for 3 months and 1.90 (IQR: −0.07–4.76) mL/min/1.73 m2/month for 1 year. Multivariate Cox regression identified baseline eGFR (HR = 0.96, 95% CI 0.95–0.98, p < 0.001) and the 3-month eGFR slope (HR = 0.79, 95% CI 0.75–0.85, p < 0.001) as independent protective factors for kidney failure. The model incorporating baseline eGFR and the 3-month eGFR slope outperformed existing risk scores for predicting renal survival. The prediction value of the eGFR slope for patient survival was also found. Both a 3-month eGFR slope >1 mL/min/1.73 m2/month (HR = 0.47, 95% CI 0.31–0.70, p < 0.001) and a 1-year eGFR slope >1 mL/min/1.73 m2/month (HR = 0.42, 95% CI 0.28–0.63, p < 0.001) were independent protective factors for patient survival. The prediction model with a 1-year eGFR slope showed a prediction ability similar to that of the classical model with kidney failure events. Conclusion: eGFR slopes are valuable predictors of renal and patients’ survival in MPO-AAGN, providing valuable prognostic information that could enhance risk stratification and clinical decision-making.