Joshua D. Bundy, PhD, MPH Department of Epidemiology Tulane University School of Public Health and Tropical Medicine and Tulane University Translational Science Institute New Orleans Louisiana

ESKD: Tulane Study Finds Excellent Performance of KFRE Score in Predicting 2-year Risk

MedicalResearch.com Interview with:

Joshua D. Bundy, PhD, MPH Department of Epidemiology Tulane University School of Public Health and Tropical Medicine and Tulane University Translational Science Institute New Orleans Louisiana

Dr. Bundy

Joshua D. Bundy, PhD, MPH
Department of Epidemiology
Tulane University School of Public Health and Tropical Medicine and
Tulane University Translational Science Institute
New Orleans Louisiana

MedicalResearch.com: What is the background for this study? What is included in the KFRE score?

Response: Kidney function is quantified using estimated glomerular filtration rate (eGFR), which is often calculated in clinical practice using filtration markers like serum creatinine and/or cystatin C, and patient characteristics like age, sex, and race. Recently, new eGFR equations were created that remove race adjustment because of concerns that using a patient’s race may perpetuate racial inequities in healthcare delivery. The Kidney Failure Risk Equation (KFRE) is the most commonly-used tool to predict end-stage kidney disease (ESKD) risk and includes age, sex, eGFR, and urinary albumin-creatinine ratio. We sought to evaluate the impact of removing race from eGFR on prediction of ESKD. 

MedicalResearch.com: What are the main findings?

Response: We found that all eGFR equations performed well in predicting 2-year risk for ESKD. However, the KFRE score better predicts 2-year risk for ESKD compared with eGFR alone, regardless of whether race adjustment is included in calculating eGFR. The new creatinine equation with age and sex may improve calibration among Black patients. 

MedicalResearch.com: What should readers take away from your report?

Response: Our results are encouraging in that they show the choice of eGFR equation does not materially affect prediction of 2-year risk for ESKD. Based on eGFR alone, however, differences in the way eGFR is calculated can substantially affect clinical decisions. Because the KFRE score incorporates more information beyond eGFR alone, it is reasonable to expect that it is less impacted by the decision to adjust for race or not. The value of the KFRE score may be an important additional consideration in addressing the current controversy surrounding the use of race in nephrology and medicine. Overall, we note that a KFRE score greater than 20% showed high sensitivity and specificity for predicting 2-year risk for ESKD and could be used for preparing kidney replacement therapy. 

MedicalResearch.com: What recommendations do you have for future research as a result of this work?

Response: While we show excellent performance of the KFRE score in predicting 2-year risk for ESKD, clinical guidelines have cited several barriers to implementation of the KFRE score in clinical practice. Clinical trials are needed to test implementation of the KFRE score. Additionally, given that the eGFR equations have been changed to remove race adjustment, new KFRE score models should be created using these new eGFR equations, which should ideally be developed and validated in racially, ethnically, and geographically diverse samples.

My co-authors and I have nothing to disclose other than funding from the US National Institutes of Health.

Citation:

Joshua D. Bundy, Katherine T. Mills, Amanda H. Anderson, et al. Prediction of End-Stage Kidney Disease Using Estimated Glomerular Filtration Rate With and Without Race: A Prospective Cohort Study. Ann Intern Med. [Epub ahead of print 11 January 2022]. doi:10.7326/M21-2928

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