ArticleJournal of nephrology2024
Real world evaluation of kidney failure risk equations in predicting progression from chronic kidney disease to kidney failure in an Australian cohort.
Article in Journal of nephrology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
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Who cites it
3 citing papers in PubMed, 1 synthesis or guideline pooled it, 3 citations in OpenAlex.
- Representation of multimorbidity and frailty in the development and validation of kidney failure prognostic prediction models: a systematic review.BMC medicine · 2024Pooled it
- External validation, recalibration, and clinical utility of the kidney failure risk equation in patients with advanced CKD: a nationwide retrospective cohort analysis in Peru.BMC nephrology · 2025Article
- Risk Stratification for CKD Progression in Primary Care.Kidney international reports · 2025Article
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Authors and funding
6 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundChronic kidney disease progression to kidney failure is diverse, and progression may be different according to genetic aspects and settings of care. We aimed to describe kidney failure risk equation prognostic accuracy in an Australian population.
methodsA retrospective cohort study was undertaken in a public hospital community-based chronic kidney disease service in Brisbane, Australia, which included a cohort of 406 adult patients with chronic kidney disease Stages 3-4 followed up over 5 years (1/1/13-1/1/18). Risk of progression to kidney failure at baseline using Kidney Failure Risk Equation models with three (eGFR/age/sex), four (add urinary-ACR) and eight variables (add serum-albumin/phosphate/bicarbonate/calcium) at 5 and 2 years were compared to actual patient outcomes.
resultsOf 406 patients followed up over 5 years, 71 (17.5%) developed kidney failure, while 112 died before reaching kidney failure. The overall mean difference between observed and predicted risk was 0.51% (p = 0.659), 0.93% (p = 0.602), and - 0.03% (p = 0.967) for the three-, four- and eight-variable models, respectively. There was small improvement in the receiver operating characteristic-area under the curve from three-variable to four-variable models: 0.888 (95%CI = 0.819-0.957) versus 0.916 (95%CI = 0.847-0.985). The eight-variable model showed marginal receiver operating characteristic-area under the curve improvement: 0.916 (95%CI = 0.847-0.985) versus 0.922 (95%CI = 0.853-0.991). The results were similar in predicting 2 year risk of kidney failure.
conclusionsThe kidney failure risk equation accurately predicted progression to kidney failure in an Australian chronic kidney disease population. Younger age, male sex, lower estimated glomerular filtration rate, higher albuminuria, diabetes mellitus, tobacco smoking and non-Caucasian ethnicity were associated with increased risk of kidney failure. Cause-specific cumulative incidence function for progression to kidney failure or death, stratified by chronic kidney disease stage, demonstrated differences within different chronic kidney disease stages, highlighting the interaction between comorbidity and outcome.
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