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Background <p>The International IgA Nephropathy (IgAN) prediction tool provides reliable risk estimates for kidney outcomes using clinical and histopathological variables. However, additional structural biomarkers may further improve prognostic precision. This study investigated whether incorporating estimated nephron number enhances the predictive performance of the International IgAN prediction tool.</p> Methods <p>We conducted a post hoc analysis of 218 adult patients with primary IgAN diagnosed with native kidney biopsy between 2007 and 2017. Nephron number per kidney was estimated by multiplying estimated kidney cortical volume derived from unenhanced computed tomography by nonsclerotic glomerular density obtained from kidney biopsy specimens. The 5&#xa0;year risk of a composite kidney outcome (≥ 50% decline in estimated glomerular filtration rate [eGFR] or initiation of kidney replacement therapy) was calculated using the International IgAN prediction tool. Discrimination and reclassification were assessed using Harrell’s C statistics, the category-free net reclassification improvement (NRI), and the integrated discrimination improvement (IDI).</p> Results <p>The cohort had a mean age of 42.6&#xa0;years, 61.5% were male, and the mean eGFR was 60.7&#xa0;mL/min/1.73 m<sup>2</sup>. The mean estimated nephron number was 6.8 × 10<sup>5</sup> per kidney. During the 5&#xa0;year follow-up, 25 patients (11.5%) reached the composite outcome. The original model showed excellent discrimination (C statistics 0.855), which improved to 0.867 after adding nephron number. The NRI significantly improved (0.544, <i>P</i> = 0.011), while the IDI showed a non-significant trend (<i>P</i> = 0.46).</p> Conclusions <p>Estimated nephron number provides additive prognostic value beyond established clinical and pathological predictors in patients with IgAN, supporting its role as a complementary biomarker in risk stratification.</p>

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Integrating nephron number into risk stratification for IgA nephropathy

  • 期刊论文

  • 发表日期：

    2026年3月27日

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  • Yuya Yamaguchi,
  • Takaya Sasaki,
  • Nobuo Tsuboi,
  • Hirokazu Marumoto,
  • Yusuke Okabayashi,
  • Kotaro Haruhara,
  • Go Kanzaki,
  • Kentaro Koike,
  • Vivette D. D’Agati,
  • John F. Bertram,
  • Toshiharu Ninomiya,
  • Takashi Yokoo

摘要

Background

The International IgA Nephropathy (IgAN) prediction tool provides reliable risk estimates for kidney outcomes using clinical and histopathological variables. However, additional structural biomarkers may further improve prognostic precision. This study investigated whether incorporating estimated nephron number enhances the predictive performance of the International IgAN prediction tool.

Methods

We conducted a post hoc analysis of 218 adult patients with primary IgAN diagnosed with native kidney biopsy between 2007 and 2017. Nephron number per kidney was estimated by multiplying estimated kidney cortical volume derived from unenhanced computed tomography by nonsclerotic glomerular density obtained from kidney biopsy specimens. The 5 year risk of a composite kidney outcome (≥ 50% decline in estimated glomerular filtration rate [eGFR] or initiation of kidney replacement therapy) was calculated using the International IgAN prediction tool. Discrimination and reclassification were assessed using Harrell’s C statistics, the category-free net reclassification improvement (NRI), and the integrated discrimination improvement (IDI).

Results

The cohort had a mean age of 42.6 years, 61.5% were male, and the mean eGFR was 60.7 mL/min/1.73 m2. The mean estimated nephron number was 6.8 × 105 per kidney. During the 5 year follow-up, 25 patients (11.5%) reached the composite outcome. The original model showed excellent discrimination (C statistics 0.855), which improved to 0.867 after adding nephron number. The NRI significantly improved (0.544, P = 0.011), while the IDI showed a non-significant trend (P = 0.46).

Conclusions

Estimated nephron number provides additive prognostic value beyond established clinical and pathological predictors in patients with IgAN, supporting its role as a complementary biomarker in risk stratification.