Dr. Benjamin Catanese is a current clinical research fellow in the Duke Division of Nephrology and a research fellow at the Duke Clinical Research Institute pursuing a Master of Health Sciences in Clinical Research. He attended medical school at New York Medical College and completed internal medicine residency at Stanford University. Dr. Catanese’s research interests center around improving outcomes at the intersection between cardiovascular disease and chronic kidney disease. His long-term goal is to become an independent investigator and clinical trialist with a focus on developing novel methods to reduce cardiovascular complications experienced by patients with chronic kidney disease. When he is not learning R programming, he enjoys spending time with his wife, two dogs, and cat, and training for marathons. Follow him @Ben_Catanese. Dr Catanese is a 2024-25 AJKD Editorial Intern.

Over recent years estimated glomerular filtration rate (eGFR) slope has become increasingly popular as a means to assess kidney function. This likely arose as it better captures the complexities of the progression of kidney disease over static eGFR measurements and avoids some of the pitfalls that lead to inaccurate estimates of static GFR such as low muscle mass. Furthermore, while low eGFR measurements have been associated with adverse outcomes, persistently declining eGFR further narrows in on a population of patients that are at particularly high risk for complications associated with kidney disease such as cardiovascular disease. In a study recently published in AJKD, Kohansal et al. explored the association of eGFR slope with progression of pre-clinic heart failure (HF) to clinical HF.

Before further discussing the results of the study, it is important to consider the areas in which eGFR slope has been gaining traction. First, decline in estimated glomerular filtration rate or eGFR slope has become a surrogate endpoint for clinical trials of chronic kidney disease (CKD) following several key studies over the last several years. In the 2023 meta-analysis by Inker et al., eGFR slope was shown to be a surrogate endpoint for kidney failure in clinical trials of CKD progression. The study analyzed data from 66 trials involving 186,312 participants across diverse disease groups, including diabetes, glomerular diseases, CKD, and cardiovascular diseases. It found a strong association between treatment effects on the total GFR slope and clinical endpoints, indicating that GFR slope could predict treatment effects on kidney failure. The findings suggested that the total GFR slope is a robust surrogate endpoint for evaluating CKD progression therapies, potentially reducing the need for long-term follow-up and facilitating earlier intervention in disease progression.

The current study fits more into the second way eGFR slope has been increasingly used in research in recent years, that is as a way to risk stratify patients depending on the rate of eGFR decline (Figure 1). Recent studies have demonstrated that more rapid decline in eGFR was associated with increased incidence of heart failure and adverse outcomes in patients with diabetes. A meta-analysis done in 2022 among patients with type 2 diabetes showed that declining eGFR slope was associated with increased risk of all-cause mortality, cardiovascular events, ESRD, and microvascular events. In building on the results of these previous studies, the current study aimed to investigate eGFR slope among patients that were at higher risk of progression to HF.

In this prospective cohort study, Kohansal et al. examined the association between declining kidney function, as measured by the eGFR slope, and the progression to clinical HF in older adults at different preclinical HF stages (Stage A: elevated risk; Stage B: cardiac abnormalities). Utilizing data from 5,362 older adults from the Atherosclerosis Risk in Communities (ARIC) study, researchers found no significant association between eGFR slope and HF progression in Stage A participants. However, among Stage B participants (those with cardiac abnormalities), a steeper annual decline in eGFR significantly increased the risk of developing HF, particularly heart failure with preserved ejection fraction (HFpEF). Individuals with the steepest eGFR decline (< -1.87 mL/min/1.73 m² per year) had a 58% higher risk of incident HF compared to those with moderate declines.

Figure 1: eGFR as a Surrogate Endpoint versus Risk Stratification Tool. © Catanese 

The findings suggest that monitoring eGFR slope is particularly valuable in identifying individuals at elevated risk for clinical HF among those already displaying preclinical cardiac abnormalities (Stage B), whereas it may not be predictive for those only at elevated risk without cardiac abnormalities (Stage A). The association between declining kidney function and HF progression was independent of baseline kidney function, cardiovascular risk factors, and medication use. The study highlights the clinical significance of tracking kidney function over time as an important predictive tool for HF progression, especially in populations already showing early cardiac structural or functional changes.

Ultimately this study, along with other recent studies investigating eGFR slope, showed that it may serve to begin risk-stratifying patients earlier than we had traditionally been able to. For instance, we may not need to wait for patients to start developing albuminuria as we do when monitoring diabetic nephropathy. Furthermore, eGFR slope may identify high-risk patients that otherwise would not be caught because they only had mild CKD with otherwise normal urinalyses.

There is now increased need to standardize the way we evaluate eGFR slope. While other studies, such as the Inker et al. study cited earlier, utilized a linear-mixed effects model just as the current investigators used, this has not been standardized in clinical practice. We frequently will evaluate changes in eGFR between appointments by evaluating graphs of eGFR, but this is typically used in a fashion like the kidney failure risk equation, to predict progression of kidney disease rather than risk of other clinical outcomes. As nephrologists if we can begin standardization of eGFR slope through larger prospective studies, then this can be used to further risk-stratify our heterogenous population and help focus our efforts on reduction in cardiovascular disease among the highest risk patients. Lastly, it will help primary care physicians understand which patients are at highest risk of adverse outcomes among their patients with mild CKD that they are managing prior to referral to nephrology.