A study has found that estimating time to kidney failure in advanced CKD can inform clinical decisions and patient counseling on prognosis.

Previous guidance for making clinical decisions in advanced chronic kidney disease (CKD) has been largely based on eGFR thresholds. However, current guidelines recommend using other tools for predicting kidney failure risk when caring for advanced CKD, such as the Kidney Failure Risk Equation (KFRE). The KFRE is a validated model for estimating 2- and 5-year risks of kidney failure using age, sex, eGFR, and urinary albumin-creatinine ratio.

“When talking to patients with advanced CKD, setting expectations on the time to kidney failure is a way of expressing prognosis that can be more intuitive to grasp when compared to using other data points,” explains Chi D. Chu, MD, MAS. “Understanding prognosis in terms of time can inform time-sensitive decisions in kidney failure preparation, such as helping guide referrals for vascular access placement in patients who opt for hemodialysis because of the lead time needed before a fistula is ready for use.”

Counseling Patients on Prognosis & Future Risks

Dr. Chu and colleagues conducted a study, published in the American Journal of Kidney Diseases, that examined associations between KFRE-predicted risk and time to kidney failure in a patients with advanced CKD who were actively followed in a nephrology clinic. “The goal of our study was to describe how eGFR and 2-year kidney failure risk using KFRE corresponded to the expected time to kidney failure,” says Dr. Chu.

The study included 1,641 patients with an eGFR lower than 60 mL/min/1.73 m² from 34 nephrology practices in the United States from 2013 to 2021. Dr. Chu and colleagues examined participants with either 2-year KFRE or eGFR. The researchers used Weibull models to estimate the median, 25th, and 75th percentile times to kidney failure starting from KFRE values of 20%, 40%, and 50%, and from eGFR values of 20, 15, and 10 mL/min/1.73 m². Over a median of 19 months follow-up, 268 participants experienced kidney failure and 180 died before reaching kidney failure.

Estimated Time to Kidney Failure Varies Widely

Across different patient characteristics, KFRE thresholds demonstrated a consistent relationship for time to kidney failure when compared with the 20 mL/min/1.73 m² eGFR threshold. Higher KFRE risk was associated with shorter time to kidney failure. The median estimated time to kidney failure varied widely across patient characteristics from an eGFR of 20 mL/min/1.73 m² and was shorter for younger patients, men, and Black individuals as well as people with diabetes, higher albuminuria, and higher blood pressure. The distribution of time to kidney failure was imprecise, highlighted by wide interquartile ranges in less advanced CKD (Figure).

“For patients with very advanced CKD, both eGFR and the KFRE provided similarly precise time estimates to kidney failure,” Dr. Chu says. “However, there is huge variability with less advanced CKD in the time that patients have before reaching kidney failure. It becomes difficult to accurately predict the time to kidney failure, especially when using only eGFR. With longer time horizons, the prognosis is more susceptible to competing events, such as death occurring before kidney failure. For patients with a short life expectancy, the discussion of CKD prognosis should also consider the possibility that the patient may never reach kidney failure in their lifetime.”

Working Toward an Effective Way to Express Prognosis

According to Dr. Chu, the findings suggest time to kidney failure can be an additional tool to help clinicians communicate prognosis and guide decision making. “Expressing prognosis in terms of time can be a helpful adjunct when discussing expectations and planning or preparing for kidney failure,” he says. “Clinicians are accustomed to synthesizing data on eGFR, albuminuria, and comorbidities to answer questions about how long patients have until they would start dialysis. Our study provides further data to support the clinical gestalt in these prognostication scenarios.”

Unanswered questions remain on how best to communicate prognosis and identify optimal decision-making strategies in a way that incorporates multiple outcomes. “We need to determine whether time correspondences can help inform time-sensitive clinical decisions in kidney failure preparation in a way that can improve outcomes,” Dr. Chu says. “Future research should also explore whether eGFR and/or KFRE thresholds should be recommended for certain clinical decisions.”