New research shows that removing a race modifier from a formula used to diagnose kidney disease could lead to more equitable care for Black patients.
New Findings to Be Highlighted at the 2022 AACC Annual Scientific Meeting CHICAGO, July 26, 2022 /PRNewswire/ -- New research shows that removing a race modifier from a formula used to diagnose kidney disease could lead to more equitable care for Black patients. This study and a second that examines how this same diagnostic approach impacts Asian patients will be presented at the 2022 AACC Annual Scientific Meeting & Clinical Lab Expo. One of the standard ways to diagnose kidney disease is by estimating glomerular filtration rate (eGFR) with a mathematical formula. Race has long been used as a variable in eGFR equations because researchers and clinicians mistakenly believed that Black people have higher muscle mass and/or creatinine metabolism than White people. The formula most widely used to determine eGFR, the Chronic Kidney Disease Epidemiology Collaboration equation (CKD-EPI), includes variables for serum creatinine, gender, race, and age. However, the National Kidney Foundation and the American Society of Nephrology now recommend that clinical laboratories use a revised CKD-EPI refit formula developed in 2021 for assessing kidney function that does not include a race modifier. Two studies discussed at 2022 AACC set out to determine how effective this new formula is. Impact of Removing Race Adjustment on Chronic Kidney Disease Staging Based on these results, the researchers support removing race as a factor in eGFR equations, noting that it perpetuates systemic racism and discrimination in healthcare, and that its removal will provide more equitable care and reduce healthcare disparities. UT Southwestern began using the new formula in May, noted Hashim. “Race is a social construct,” he said. “By removing race as a variable, patients are now objectively classified, which opens access for additional testing and more investigation into their condition. This can only lead to better care for patients with chronic kidney disease. This is very significant because we know there is racial disparity in healthcare. By removing race as a factor, medicine becomes more personalized.” Accuracy of the New eGFR Equation in Korea This means that “additional research is needed to decide whether to apply the 2021 CKD-EPI equation in clinical practice” with Asian patients, said Tae-Dong Jeong, MD, PhD, the lead author of the study and a researcher with Ewha Womans University College of Medicine in Seoul. Abstract Information AACC Annual Scientific Meeting registration is free for members of the media. Reporters can register online here: https://www.xpressreg.net/register/aacc0722/media/landing.asp A-029 Impact of removing race adjustment when estimating GFR on chronic kidney disease staging and A-109 Accuracy of the new creatinine based equation to estimate glomerular filtration rate without race in Korea will be presented during: Scientific Poster Session About the 2022 AACC Annual Scientific Meeting & Clinical Lab Expo The AACC Annual Scientific Meeting offers 5 days packed with opportunities to learn about exciting science from July 24-28. Plenary sessions will explore artificial intelligence-based clinical prediction models, advances in multiplex technologies, human brain organogenesis, building trust between the public and healthcare experts, and direct mass spectrometry techniques. At the AACC Clinical Lab Expo, more than 750 exhibitors will fill the show floor of the McCormick Place Convention Center in Chicago with displays of the latest diagnostic technology, including but not limited to COVID-19 testing, artificial intelligence, mobile health, molecular diagnostics, mass spectrometry, point-of-care, and automation. About AACC Christine DeLong Molly Polen View original content to download multimedia:https://www.prnewswire.com/news-releases/breaking-research-could-reduce-healthcare-disparities-by-making-kidney-disease-diagnosis-and-treatment-more-equitable-301592083.html SOURCE AACC |