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

Investigators Find Removing Race Coefficient from CKD-EPI Equation Would Introduce Bias Rather Than Improve Accuracy

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

Dr. Chi-yuan Hsu

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.

MedicalResearch.com: What are the main findings?

Response: We believe that Zelnick et al came to their conclusion due to implementation of an improper statistical analysis that stratified data by GFR measured using iothalamate clearance rather than by estimated GFR.

Our analysis shows that the current equations using serum creatinine to estimate kidney function have no systematic error for self-identified Black individuals compared to non-Black individuals.

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

Response: While we share in the ultimate goal of eliminating race from equations used to estimate kidney function, we did not observe bias in the use of the CKD-EPI eGFR equation that includes a coefficient for race among Black participants with an eGFR <45 ml/min/1.73m2.  Further, removing the race coefficient from the CKD-EPI equation would introduce bias rather than improve its accuracy.

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

Response: If we are going to continue to rely on serum creatinine to assess kidney function, we need to better understand why multiple studies have consistently shown that, on average, for any given age, sex and level of measured kidney function, adult Americans who self-identified as being Black have higher serum creatinine concentrations than adult Americans who do not so identify.

We think there should be more research into alternative approaches that do not rely on serum creatinine.

MedicalResearch.com: Is there anything else you would like to add?

Response: We have no directly relevant financial conflicts of interest to disclosure. We are conducting our own separate analysis of the Chronic Renal Insufficiency Cohort study data to write a full-length manuscript (not a Research Letter) on the topic of race and kidney function estimation.

Citation:

Hsu C, Yang W, Go AS, Parikh RV, Feldman HI. Analysis of Estimated and Measured Glomerular Filtration Rates and the CKD-EPI Equation Race Coefficient in the Chronic Renal Insufficiency Cohort Study. JAMA Netw Open. 2021;4(7):e2117080. doi:10.1001/jamanetworkopen.2021.17080

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Jul 17, 2021 @ 10:58 am

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