ArticleBMC nephrology2019
Validation of the kidney failure risk equation for end-stage kidney disease in Southeast Asia.
Article in BMC nephrology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.
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Who cites it
15 citing papers in PubMed, 1 synthesis or guideline pooled it, 34 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
- Artificial intelligence in nephrology: predicting CKD progression and personalizing treatment.International urology and nephrology · 2026Review
- 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
- Factors affecting disease progression in early-stage chronic kidney disease in a multi-ethnic, southeast Asian primary care population.Frontiers in medicine · 2025Article
- Article
- Risk Prediction and Management of Chronic Kidney Disease in People Living with Type 2 Diabetes Mellitus.Diabetes & metabolism journal · 2024Review
- Article
- Clinical Decision Support Tools in the Electronic Medical Record.Kidney international reports · 2024Review
- Predictive Value of Kidney Failure Risk Equation and Neutrophil Gelatinase-Associated Lipocalin for Chronic Kidney Disease Progression in Chinese Population - A Retrospective Study.International journal of general medicine · 2024Article
- Recalibrating the kidney failure risk equation for a Mediterranean European population: reducing age and sex inequality.Frontiers in medicine · 2024Article
- The kidney failure risk equation predicts kidney failure: Validation in an Australian cohort.Nephrology (Carlton, Vic.) · 2023Article
- Machine learning to predict end stage kidney disease in chronic kidney disease.Scientific reports · 2022Article
- Healthcare professionals' perspectives on facilitators of and barriers to CKD management in primary care: a qualitative study in Singapore clinics.BMC health services research · 2022Article
- Multi-Center Health Informatics to Examine the Implementation of Guideline-Directed Medical Therapy in Chronic Kidney Disease.Journal of primary care & community healthArticle
- The Kidney Failure Risk Equation for Prediction of Allograft Loss in Kidney Transplant Recipients.Kidney medicineArticle
Corrections and comments
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Authors and funding
6 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPatients with chronic kidney disease (CKD) are at high risk of end-stage kidney disease (ESKD). The Kidney Failure Risk Equation (KFRE), which predicts ESKD risk among patients with CKD, has not been validated in primary care clinics in Southeast Asia (SEA). Therefore, we aimed to (1) evaluate the performance of existing KFRE equations, (2) recalibrate KFRE for better predictive precision, and (3) identify optimally feasible KFRE thresholds for nephrologist referral and dialysis planning in SEA.
methodsAll patients with CKD visiting nine primary care clinics from 2010 to 2013 in Singapore were included and applied 4-variable KFRE equations incorporating age, sex, estimated glomerular filtration rate (eGFR), and albumin-to-creatinine ratio (ACR). ESKD onset within two and five years were acquired via linkage to the Singapore Renal Registry. A weighted Brier score (the squared difference between observed vs predicted ESKD risks), bias (the median difference between observed vs predicted ESKD risks) and precision (the interquartile range of the bias) were used to select the best-calibrated KFRE equation.
resultsThe recalibrated KFRE (named Recalibrated Pooled KFRE SEA) performed better than existing and other recalibrated KFRE equations in terms of having a smaller Brier score (square root: 2.8% vs. 4.0-9.3% at 5 years; 2.0% vs. 6.1-9.1% at 2 years), less bias (2.5% vs. 3.3-5.2% at 5 years; 1.8% vs. 3.2-3.6% at 2 years), and improved precision (0.5% vs. 1.7-5.2% at 5 years; 0.5% vs. 3.8-4.2% at 2 years). Area under ROC curve for the Recalibrated Pooled KFRE SEA equations were 0.94 (95% confidence interval [CI]: 0.93 to 0.95) at 5 years and 0.96 (95% CI: 0.95 to 0.97) at 2 years. The optimally feasible KFRE thresholds were > 10-16% for 5-year nephrologist referral and > 45% for 2-year dialysis planning. Using the Recalibrated Pooled KFRE SEA, an estimated 82 and 89% ESKD events were included among 10% of subjects at highest estimated risk of ESKD at 5-year and 2-year, respectively.
conclusionsThe Recalibrated Pooled KFRE SEA performs better than existing KFREs and warrants implementation in primary care settings in SEA.
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