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Established the first clinical prediction model regarding the risk of hyperuricemia in adult IgA nephropathy

  • Nephrology - Original Paper
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Abstract

Objective

To construct a novel nomogram model that predicts the risk of hyperuricemia incidence in IgA nephropathy (IgAN).

Methods

Demographic and clinicopathological characteristics of 1184 IgAN patients in the First Affiliated Hospital of Zhengzhou University Hospital were collected. Univariate analysis and multivariate logistic regression were used to screen out hyperuricemia risk factors. The risk factors were used to establish a predictive nomogram model. The performance of the nomogram model was evaluated using an area under the receiver-operating characteristic curve (AUC), calibration plots, and a decision curve analysis.

Results

Independent predictors for hyperuricemia incidence risk included sex, hypoalbuminemia, hypertriglyceridemia, blood urea nitrogen (BUN), estimated glomerular filtration rate (eGFR), 24 h urinary protein (24 h TP), gross hematuria and tubular atrophy/interstitial fibrosis (T). The nomogram model exhibited moderate prediction ability with an AUC of 0.834 (95% CI 0.804–0.864). The AUC from validation reached 0.787 (95% CI 0.736–0.839). The decision curve analysis displayed that the hyperuricemia risk nomogram was clinically applicable.

Conclusion

Our novel and simple nomogram containing 8 factors may be useful in predicting hyperuricemia incidence risk in IgAN.

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Data availability

All relevant data during this study are included in this article. Further enquiries can be directed to the corresponding author.

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Funding

YFL received a National Natural Science Foundation of China (81701601). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Authors and Affiliations

  1. Department of Nephrology, The First Affiliated Hospital of Zhengzhou University, 1 Jianshe East Road, Zhengzhou, 450052, Henan, China

    Yin-Hong Geng, Zhe Zhang, Jun-Jun Zhang, Bo Huang, Zui-Shuang Guo, Xu-Tong Wang, Song-Xia Quan, Rui-Min Hu & Ya-Fei Liu

  2. Department of Nephrology, The First Affiliated Hospital of Henan University of Traditional Chinese Medicine, 19 Renmin Road, Zhengzhou, 450046, Henan, China

    Lin-Qi Zhang

  3. Department of Pediatrics, The First Affiliated Hospital of Henan University of Traditional Chinese Medicine, 19 Renmin Road, Zhengzhou, 450046, Henan, China

    Chun-Dong Song & Feng-Yang Duan

Authors
  1. Yin-Hong Geng
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  2. Zhe Zhang
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  3. Jun-Jun Zhang
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  4. Bo Huang
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  5. Zui-Shuang Guo
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  6. Xu-Tong Wang
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  7. Lin-Qi Zhang
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  8. Song-Xia Quan
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  9. Rui-Min Hu
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  10. Chun-Dong Song
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  11. Feng-Yang Duan
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  12. Ya-Fei Liu
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Contributions

Data curation: ZZ, BH, and Z-SG. Formal analysis: Y-HG. Investigation: ZZ, S-XQ, and C-DS. Supervision: Y-FL, X-TW, R-MH, and F-YD. Writing—original draft: Y-HG. Writing—review and editing: J-JZ, L-QZ, and Y-FL.

Corresponding author

Correspondence to Ya-Fei Liu.

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Conflict of interest

The authors have no conflicts of interest to declare availability of data and material.

Ethical approval

It was approved by the First Affiliated Hospital of Zhengzhou University Hospital Ethics Committee (Ethical review number: 2022-KY-0048-002).

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Geng, YH., Zhang, Z., Zhang, JJ. et al. Established the first clinical prediction model regarding the risk of hyperuricemia in adult IgA nephropathy. Int Urol Nephrol 55, 1787–1797 (2023). https://doi.org/10.1007/s11255-023-03498-0

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  • DOI: https://doi.org/10.1007/s11255-023-03498-0

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