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Original ArticlesGlomerular and Tubulointerstitial Diseases
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External Validation of the International IgA Nephropathy Prediction Tool

Junjun Zhang, Bo Huang, Zhangsuo Liu, Xutong Wang, Minhua Xie, Ruxue Guo, Yongli Wang, Dan Yu, Panfei Wang, Yuze Zhu and Jingjing Ren
CJASN August 2020, 15 (8) 1112-1120; DOI: https://doi.org/10.2215/CJN.16021219
Junjun Zhang
1Department of Nephrology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, People’s Republic of China
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Bo Huang
1Department of Nephrology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, People’s Republic of China
2Academy of Medical Science, Zhengzhou University, Zhengzhou, People’s Republic of China
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Zhangsuo Liu
1Department of Nephrology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, People’s Republic of China
3Research Institute of Nephrology, Zhengzhou University, Zhengzhou, People’s Republic of China
4Key Laboratory of Precision Diagnosis and Treatment for Chronic Kidney Disease in Henan Province, Zhengzhou, People’s Republic of China
5Core Unit of National Clinical Medical Research Center of Kidney Disease, Zhengzhou, People’s Republic of China
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  • ORCID record for Zhangsuo Liu
Xutong Wang
1Department of Nephrology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, People’s Republic of China
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Minhua Xie
1Department of Nephrology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, People’s Republic of China
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Ruxue Guo
1Department of Nephrology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, People’s Republic of China
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Yongli Wang
1Department of Nephrology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, People’s Republic of China
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Dan Yu
1Department of Nephrology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, People’s Republic of China
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Panfei Wang
1Department of Nephrology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, People’s Republic of China
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Yuze Zhu
1Department of Nephrology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, People’s Republic of China
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Jingjing Ren
1Department of Nephrology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, People’s Republic of China
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Abstract

Background and objectives The International IgA Nephropathy Network recently developed and externally validated two models to predict the risk of progression of IgA nephropathy: full models without and with race. This study sought to externally validate the International IgA Nephropathy Prediction Tool in a large, independent, and contemporary cohort in China.

Design, setting, participants, & measurements We included 1373 patients with biopsy-confirmed primary IgA nephropathy from The First Affiliated Hospital of Zhengzhou University from January 2012 to May 2018 and calculated predicted risks for each patient. The outcomes of interest were a 50% decline in eGFR or kidney failure. We assessed the performance of both models using discrimination (concordance statistics and Kaplan–Meier curves between subgroups), calibration (calibration plots), reclassification (net reclassification improvement and integrated discrimination improvement), and clinical utility (decision curve analysis).

Results The median follow-up was 29 months (interquartile range, 21–43 months; range, 1–95 months), and 186 (14%) patients reached the kidney outcomes of interest. Both models showed excellent discrimination (concordance statistics >0.85 and well separated survival curves). Overall, the full model without race generally underestimated the risk of primary outcome, whereas the full model with race was well calibrated for predicting 5-year risk. Compared with the full model without race, the full model with race had significant improvement in reclassification, as assessed by the net reclassification improvement (0.49; 95% confidence interval, 0.41 to 0.59) and integrated discrimination improvement (0.06; 95% confidence interval, 0.04 to 0.08). Decision curve analysis showed that both full models had a higher net benefit than default strategies, and the model with race performed better.

Conclusions In this study, both full models demonstrated remarkable discrimination, acceptable calibration, and satisfactory clinical utility. The relatively short follow-up time may have limited the validation of these models.

  • IgA nephropathy
  • external validation
  • international prediction tool
  • glomerular filtration rate
  • Glomerulonephritis
  • IGA
  • Calibration
  • Kidney Failure
  • Chronic
  • Cohort Studies
  • Biopsy
  • Received December 31, 2019.
  • Accepted May 28, 2020.
  • Copyright © 2020 by the American Society of Nephrology
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Clinical Journal of the American Society of Nephrology: 15 (8)
Clinical Journal of the American Society of Nephrology
Vol. 15, Issue 8
August 07, 2020
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External Validation of the International IgA Nephropathy Prediction Tool
Junjun Zhang, Bo Huang, Zhangsuo Liu, Xutong Wang, Minhua Xie, Ruxue Guo, Yongli Wang, Dan Yu, Panfei Wang, Yuze Zhu, Jingjing Ren
CJASN Aug 2020, 15 (8) 1112-1120; DOI: 10.2215/CJN.16021219

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External Validation of the International IgA Nephropathy Prediction Tool
Junjun Zhang, Bo Huang, Zhangsuo Liu, Xutong Wang, Minhua Xie, Ruxue Guo, Yongli Wang, Dan Yu, Panfei Wang, Yuze Zhu, Jingjing Ren
CJASN Aug 2020, 15 (8) 1112-1120; DOI: 10.2215/CJN.16021219
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Keywords

  • IgA nephropathy
  • external validation
  • international prediction tool
  • glomerular filtration rate
  • glomerulonephritis
  • IGA
  • Calibration
  • Kidney Failure
  • Chronic
  • Cohort Studies
  • Biopsy

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