Prognostic Performance of the 2-Year Kidney Failure Risk Equation and Kidney Replacement Therpay (KRT) Preparedness in Advanced CKD: Resolving Spectrum Bias in a Malaysian Cohort
In a Malaysian tertiary cohort, the 2-year Kidney Failure Risk Equation (KFRE) demonstrated superior prognostic discrimination over eGFR for predicting end-stage kidney disease progression in earlier CKD stages but required regional recalibration to correct systematic overprediction, while the high rate of catheter-dependent dialysis initiation highlighted persistent challenges in timely KRT preparedness.
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Chronic kidney disease is a condition where the body's filters, the kidneys, slowly lose their ability to clean the blood. As this function declines, toxins build up, and eventually, the kidneys stop working entirely, a state known as end-stage kidney disease. When this happens, patients face a critical choice: they must either undergo dialysis, a process that mechanically filters the blood, or receive a kidney transplant. For years, doctors have relied on a single number to decide when to start preparing a patient for this transition. This number, called the estimated glomerular filtration rate, or eGFR, measures how well the kidneys are filtering at a specific moment. However, this snapshot can be misleading. A patient with a low number might have a slow decline and years to prepare, while another with a similar number might deteriorate rapidly. This uncertainty often leads to referrals for education and surgery happening too late, leaving patients with little time to make informed choices or for surgeons to create the necessary access points for treatment.
To address this, researchers have developed a more comprehensive tool called the Kidney Failure Risk Equation. Instead of looking at kidney function alone, this tool combines a patient's age, sex, kidney function, and the amount of protein in their urine to predict the likelihood of kidney failure within the next two years. While this equation has been tested extensively in other parts of the world, its performance in Malaysia remained unclear. A team of researchers at the University Malaya Medical Centre set out to see if this tool works as well for Malaysian patients and whether it can help doctors identify those who need urgent preparation for kidney replacement therapy. They analyzed the records of 245 adults who had already been referred for kidney education, tracking their progress until mid-2026 to see who actually reached kidney failure and how they were treated.
The study revealed that while the traditional method of using kidney function numbers alone works reasonably well for patients who are already very sick, it fails to distinguish risk among those in the earlier stages of advanced disease. In the group of patients who were not yet at the very final stage, the old method was no better than random guessing at predicting who would fail soon. In contrast, the new risk equation provided a clearer picture, successfully identifying which patients were likely to progress faster. This distinction is vital because it offers a window of opportunity. If doctors can identify high-risk patients earlier, they have time to discuss treatment options and schedule surgeries to create a permanent access point, such as a fistula, which requires weeks or months to heal and mature before it can be used.
However, the researchers found that the equation, as it was originally written, tended to overestimate the risk for many patients in their cohort. The mathematical model predicted that more people would reach kidney failure than actually did, particularly those in the lower and middle risk groups. This suggests that the equation needs to be adjusted to fit the specific health patterns and demographics of the Malaysian population before it can be used to make precise predictions for individuals. Without this local adjustment, the tool might cause unnecessary alarm or lead to premature medical interventions for patients who would have remained stable for longer.
Despite the improved ability to predict risk, the study highlighted a persistent and troubling reality in patient care: many people are still referred for help too late. More than half of the patients in this study were already at the most advanced stage of kidney disease when they first met with educators. Consequently, when these patients eventually needed dialysis, the majority had to start with a temporary tube inserted into a large vein in their neck or chest, rather than a permanent, surgically created connection. This temporary method is less ideal and carries higher risks of infection and complications. The data showed that only about a quarter of those starting dialysis had a mature, permanent access point ready. This outcome indicates that even with a better tool to predict who is at risk, the current system of referring patients often fails to provide enough time for the necessary surgical planning to take place.
The researchers concluded that while the risk equation is a powerful tool for understanding who is likely to fail soon, it cannot fix the problem of late referrals on its own. The equation works best when it is recalibrated to match local data, ensuring it does not overstate the danger for patients. More importantly, the study suggests that the entire process needs to start earlier. If the risk equation is integrated into the healthcare system to trigger referrals at the first sign of significant risk, rather than waiting until kidney function drops to a critical low, patients could gain the months of lead time needed to prepare properly. Until such systemic changes occur, the gap between predicting risk and being ready for treatment will remain a significant challenge, leaving many patients to begin their dialysis journey with temporary, less optimal solutions.
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