Author Interviews, Kidney Disease, Race/Ethnic Diversity / 13.01.2022

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 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.  (more…)
Author Interviews, JAMA, Kidney Disease, Race/Ethnic Diversity, UCSF / 17.07.2021

MedicalResearch.com Interview with: Chi-yuan Hsu, MD, MSc (he/him/his) Professor and Division Chief Division of Nephrology University of California, San Francisco San Francisco, CA 94143-0532 MedicalResearch.com: What is the background for this study? Response: There has been a great deal of controversy recently about how race should be considered in medicine, including its use in estimating kidney function (e.g. https://jamanetwork.com/journals/jama/fullarticle/2769035).  A recent paper published in JAMA Network Open by Zelnick et al suggested that removing the race coefficient improves the accuracy of estimating kidney function (https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2775076) in the Chronic Renal Insufficiency Cohort, a NIH-funded study (www.cristudy.org). We are core investigators of the Chronic Renal Insufficiency Cohort Study and were not involved in the Zelnick’s study that was based on a public use dataset.  Because we were surprised by the methodological approach they took and the conclusion they came to, we implemented our own analysis of the data. (more…)