Which prognostic model predicts kidney failure best? A comprehensive external validation study in patients with advanced chronic kidney disease, accounting for the competing risk of mortality

Chava Ramspek*, Samantha L Hayward, Fergus J Caskey, et al.

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

Abstract

Background
Various prediction models have been developed to predict the risk of kidney failure in patients with chronic kidney disease. However, guideline recommended models have yet to be compared head-to-head, validation in advanced chronic kidney disease (CKD) patients is lacking, and most models don’t account for competing risks. The aim of the current study is to externally validate 11 existing models of kidney failure in two large cohorts of advanced CKD patients, whilst taking the competing risk of death into account.

Methods
The models were validated in EQUAL, a European prospective cohort of older advanced CKD patients and the Swedish Renal Registry (SRR) of nephrology-referred CKD patients. Model performance was assessed with discrimination and calibration.

Results
1580 patients from EQUAL and 13489 patients from the SRR were included. The average C-statistic over the 11 validated models was 0.74 in EQUAL and 0.80 in the SRR compared to 0.89 in previous validations. Most models with longer prediction-horizons overestimated the risk of kidney failure considerably. The 5-year Kidney Failure Risk Equation (KFRE) overpredicted risk by 10% -18%. The 4 and 8 variable 2-year KFRE and the 4-year Grams model showed excellent calibration and good discrimination in both cohorts.

Conclusion
Existing models can accurately predict kidney failure in patients with advanced CKD. For a shorter time-frame of 2 years, the KFRE had a good performance despite the fact that this model does not account for competing events. However, models that predicted over a longer time-frame of 5 years overestimated risk due to the competing risk of death.
Original languageEnglish
JournalJournal of the American Society of Nephrology
Publication statusAccepted/In press - 27 Dec 2020

Keywords

  • comprehensive external validation
  • chronic kidney disease
  • kidney failure
  • prediction model
  • prognostic

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