BMC Nephrology (Sep 2021)

Nomogram predicting the risk of three-year chronic kidney disease adverse outcomes among East Asian patients with CKD

  • Huizhen Ye,
  • Youyuan Chen,
  • Peiyi Ye,
  • Yu Zhang,
  • Xiaoyi Liu,
  • Guanqing Xiao,
  • Zhe Zhang,
  • Yaozhong Kong,
  • Gehao Liang

DOI
https://doi.org/10.1186/s12882-021-02496-7
Journal volume & issue
Vol. 22, no. 1
pp. 1 – 9

Abstract

Read online

Abstract Background Chronic kidney disease (CKD) is a common health challenge. There are some risk models predicting CKD adverse outcomes, but seldom focus on the Mongoloid population in East Asian. So, we developed a simple but intuitive nomogram model to predict 3-year CKD adverse outcomes for East Asian patients with CKD. Methods The development and internal validation of prediction models used data from the CKD-ROUTE study in Japan, while the external validation set used data collected at the First People’s Hospital of Foshan in southern China from January 2013 to December 2018. Models were developed using the cox proportional hazards model and nomogram with SPSS and R software. Finally, the model discrimination, calibration and clinical value were tested by R software. Results The development and internal validation data-sets included 797 patients (191 with progression [23.96%]) and 341 patients (89 with progression [26.10%]), respectively, while 297 patients (108 with progression [36.36%]) were included in the external validation data set. The nomogram model was developed with age, eGFR, haemoglobin, blood albumin and dipstick proteinuria to predict three-year adverse-outcome-free probability. The C-statistics of this nomogram were 0.90(95% CI, 0.89–0.92) for the development data set, 0.91(95% CI, 0.89–0.94) for the internal validation data set and 0.83(95% CI, 0.78–0.88) for the external validation data-set. The calibration and decision curve analyses were good in this model. Conclusion This visualized predictive nomogram model could accurately predict CKD three-year adverse outcomes for East Asian patients with CKD, providing an easy-to-use and widely applicable tool for clinical practitioners.

Keywords