Nephron Number Improves Prediction of Kidney Outcomes in IgAN

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Background: We estimated nephron number by combining kidney cortical volume estimated from non-contrast computed tomography with glomerular density obtained from kidney biopsy specimens among patients with IgA nephropathy. Whether the addition of nephron number improves predictability of a widely-validated International IgA Nephropathy Prediction Tool has not yet been investigated. We aimed to (i) validate the prediction tool in a Japanese cohort of patients with IgA nephropathy and (ii) assess the improvement of predictability by incorporating nephron number. Methods: We analyzed patients with biopsy-proven IgA nephropathy whose nephron number was estimated by multiplying kidney cortical volume by non-sclerotic glomerular density. Predicted risk was assessed using the International Prediction Tool. The primary endpoint was a 50% decline in eGFR or kidney replacement therapy. Predictive performance was assessed using Harrell’s C-statistics, net reclassification improvement (NRI) and integrated discrimination improvement (IDI). Results: We analyzed 218 patients (mean age 42.7 years, 61.7% male). Average nephron number was 680,000 (SD 390,000). During 5-year follow-up, 25 patients (11.5%) reached the composite endpoint. As shown in the Table, original prediction tool demonstrated good discrimination (C-statistics, 0.855). Incorporating nephron number into the model improved the predictive performance (C-statistics, 0.867; NRI, 0.544; IDI, 0.015). Conclusion: The International IgA Nephropathy Prediction Tool demonstrated robust predictive performance in a Japanese cohort. Incorporation of the estimated nephron number enhanced risk discrimination, suggesting that nephron number may offer meaningful incremental prognostic value in the management of IgA nephropathy. Risk prediction performance of the International Prediction Tool with nephron number - Model Harrell’s C-statistic NRI (95% CI) IDI (95% CI) International Prediction Tool 0.855 – – + Nephron Number 0.867 0.544 (0.144, 0.944)* 0.015 (-0.025, 0.055) *P = 0.011 CI, confidence interval; NRI, net reclassification improvement; IDI, integrated discrimination improvement.

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