Abstract
Introduction:
Chronic kidney disease (CKD) is highly prevalent in Thailand and imposes a growing burden on the health system, driven by limited nephrology capacity and high rates of unplanned dialysis. The kidney failure risk equation (KFRE) estimates the risk of progression to kidney failure (KF) on age, sex, estimated glomerular filtration rate (eGFR) and urine albumin-to-creatinine ratio. This study aims to validate and, if required, recalibrate the four-variable KFRE for the Thai population and to assess the potential impact of KFRE-guided referral strategies on clinical care and health system performance.
Methods and analysis:
We will conduct a retrospective cohort study using linked, de-identified national health databases covering approximately 70% of the Thai population. Adult patients with CKD stages 3–5 will be included. KFRE performance will be evaluated at 2 and 5 years for discrimination and calibration. If miscalibration is identified, the model will be recalibrated using Cox-based methods. Simulations (1000 iterations) indicated that approximately 920 KF events by 5 years would be required to achieve the target standard errors for the calibration slope. A subsequent impact analysis will compare KFRE-guided referral with current Thai CKD guideline criteria and real-world practice using a decision-tree and Markov modelling framework.
Ethics and dissemination:
Ethical approval was obtained from the Ethics Committee of the Institute for the Development of Human Research Protections, Thailand (COA No. IHRP2025110), Imperial College London and the London School of Hygiene and Tropical Medicine. The requirement for informed consent was waived due to the use of anonymised secondary data. Findings will be disseminated through peer-reviewed publications, conferences and policy briefs to supplement evidence-based referral strategies and health system planning.
Chronic kidney disease (CKD) is highly prevalent in Thailand and imposes a growing burden on the health system, driven by limited nephrology capacity and high rates of unplanned dialysis. The kidney failure risk equation (KFRE) estimates the risk of progression to kidney failure (KF) on age, sex, estimated glomerular filtration rate (eGFR) and urine albumin-to-creatinine ratio. This study aims to validate and, if required, recalibrate the four-variable KFRE for the Thai population and to assess the potential impact of KFRE-guided referral strategies on clinical care and health system performance.
Methods and analysis:
We will conduct a retrospective cohort study using linked, de-identified national health databases covering approximately 70% of the Thai population. Adult patients with CKD stages 3–5 will be included. KFRE performance will be evaluated at 2 and 5 years for discrimination and calibration. If miscalibration is identified, the model will be recalibrated using Cox-based methods. Simulations (1000 iterations) indicated that approximately 920 KF events by 5 years would be required to achieve the target standard errors for the calibration slope. A subsequent impact analysis will compare KFRE-guided referral with current Thai CKD guideline criteria and real-world practice using a decision-tree and Markov modelling framework.
Ethics and dissemination:
Ethical approval was obtained from the Ethics Committee of the Institute for the Development of Human Research Protections, Thailand (COA No. IHRP2025110), Imperial College London and the London School of Hygiene and Tropical Medicine. The requirement for informed consent was waived due to the use of anonymised secondary data. Findings will be disseminated through peer-reviewed publications, conferences and policy briefs to supplement evidence-based referral strategies and health system planning.
| Original language | English |
|---|---|
| Article number | e114382 |
| Number of pages | 8 |
| Journal | BMJ Open |
| Volume | 16 |
| Issue number | 5 |
| DOIs | |
| Publication status | Published - 15 May 2026 |
Bibliographical note
Publisher Copyright:© Author(s) (or their employer(s)) 2026.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Health economics
- Chronic renal failure
- Risk Assessment
- Health policy
- Clinical Decision-Making
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