Scholarlink

Background <p>The highly variable clinical progression of IgA nephropathy (IgAN) makes it challenging to accurately predict the risk of disease deterioration in patients. Although elevated single-nephron estimated glomerular filtration rate (eGFR) is implicated in disease progression, its prognostic utility remains underexplored due to methodological limitations in nephron quantification. This study aims to fill this research gap by establishing single-nephron eGFR as a prognostic factor and developing a predictive nomogram for assessing kidney disease progression in IgAN patients.</p> Methods <p>We included 190 patients with biopsy-proven IgAN undergoing kidney biopsy and CT imaging. Single-nephron eGFR was calculated by dividing eGFR by nephron number, derived from cortical volume and glomerular density. A Cox model incorporating clinical, pathological, and single-nephron eGFR parameters was developed (training cohort: n = 133) and validated (validation cohort: n = 57). Kidney function decline was defined as an annual eGFR decrease ≥5 ml/min/1·73 m<sup>2</sup>, ≥40% eGFR reduction, or end-stage renal disease. Model performance was assessed using Harrell’s C-index, time-dependent AUC, and calibration curves.</p> Results <p>Of the 410 patients screened, 190 (46%) met the eligibility criteria. The cohort was 55% male patients, with a median age of 36 years (IQR, 30–47). The median follow-up duration was 37 months (IQR, 22–48). The nomogram included smoking history, eGFR, use of calcium channel blockers, and single-nephron eGFR. It demonstrated good discrimination (C-index 0.76 [0.69–0.82] in training; 0.75 [0.65–0.85] in validation) with good calibration. Low-risk patients had significantly longer survival compared to high-risk patients in both the development (<i>P</i> &lt; 0.001) and validation (<i>P</i> = 0.04) cohorts. An interactive Shiny app was developed for clinical use (https://yangchenkay.shinyapps.io/IgAN/).</p> Conclusions <p>This study develops a clinically applicable prediction model for IgAN that underscores the prognostic value of single-nephron eGFR in renal outcome and enables effective risk stratification of kidney function decline in patients with IgAN.</p> Clinical trial number <p>Not applicable.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Development and validation of a single-nephron estimated glomerular filtration rate model to predict disease progression in IgA nephropathy

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年11月5日

查看全文
  • Chen Yang,
  • Shuang Liang,
  • Zhi-Yu Duan,
  • Shu-Wei Duan,
  • Jie Wu,
  • Zhe Feng,
  • Pu Chen,
  • Xiang-Mei Chen,
  • Yong Wang,
  • Guang-Yan Cai

摘要

Background

The highly variable clinical progression of IgA nephropathy (IgAN) makes it challenging to accurately predict the risk of disease deterioration in patients. Although elevated single-nephron estimated glomerular filtration rate (eGFR) is implicated in disease progression, its prognostic utility remains underexplored due to methodological limitations in nephron quantification. This study aims to fill this research gap by establishing single-nephron eGFR as a prognostic factor and developing a predictive nomogram for assessing kidney disease progression in IgAN patients.

Methods

We included 190 patients with biopsy-proven IgAN undergoing kidney biopsy and CT imaging. Single-nephron eGFR was calculated by dividing eGFR by nephron number, derived from cortical volume and glomerular density. A Cox model incorporating clinical, pathological, and single-nephron eGFR parameters was developed (training cohort: n = 133) and validated (validation cohort: n = 57). Kidney function decline was defined as an annual eGFR decrease ≥5 ml/min/1·73 m2, ≥40% eGFR reduction, or end-stage renal disease. Model performance was assessed using Harrell’s C-index, time-dependent AUC, and calibration curves.

Results

Of the 410 patients screened, 190 (46%) met the eligibility criteria. The cohort was 55% male patients, with a median age of 36 years (IQR, 30–47). The median follow-up duration was 37 months (IQR, 22–48). The nomogram included smoking history, eGFR, use of calcium channel blockers, and single-nephron eGFR. It demonstrated good discrimination (C-index 0.76 [0.69–0.82] in training; 0.75 [0.65–0.85] in validation) with good calibration. Low-risk patients had significantly longer survival compared to high-risk patients in both the development (P < 0.001) and validation (P = 0.04) cohorts. An interactive Shiny app was developed for clinical use (https://yangchenkay.shinyapps.io/IgAN/).

Conclusions

This study develops a clinically applicable prediction model for IgAN that underscores the prognostic value of single-nephron eGFR in renal outcome and enables effective risk stratification of kidney function decline in patients with IgAN.

Clinical trial number

Not applicable.