Population Health News

Removing Race from Kidney Function Evaluation Causes Health Disparities

Researchers found that excluding race from kidney function evaluation could impact cancer treatment for Black patients, creating health disparities.

chronic disease health disparities racial disparities

Source: Getty Images

By Erin McNemar, MPA

- Excluding race as a factor from the Chronic Kidney Disease-Epidemiology Collaboration (CKD-EPI) equation used to guide cancer treatment doses and eligibility could decrease the proportion of Black patients recommend to receive full doses of anticancer drugs, creating health disparities in healthcare.

Researchers from the University of Pittsburgh, National Cancer Institute, and UPMC Hillman Cancer Center conducted the retrospective analysis of 15 years of phase 1 clinical trial data. The CKD-EPI equation estimates a key component of kidney function called glomerular filtration rate (GFR).

Historically, the CKD-EPI equation has calculated a higher GFR for Black patients. However, with the use of race in kidney function-estimating equations coming into question, researchers are discussing the possible consequences of removing race from equations that calculate GFR.

Clinicians use the CKD-EPI equation to determine the eligibility of kidney cancer patients and the dosage of anticancer medications. Before this study, no analysis has examined the potential impact of removing race from the CKD-EPI equation on cancer treatment.

However, the researchers’ findings suggest that removing race from the CKD-EPI equation could decrease the proportion of Black patients eligible to receive anticancer medications.

“Our findings suggest that removing race as a variable in the CKD-EPI equation – a widely used equation for estimating kidney function – could impact care for Black cancer patients. Specifically, removing race may exclude more Black patients, who are already disproportionately affected by cancer, from receiving full doses of potentially life-saving cancer therapy, which could affect their outcomes,” study co-author Dr. Thomas D. Nolin said in a press release.

“We hope our research can enhance wider discussions around race-based adjustments that will explore the complexities of including or removing race factors from treatment considerations. Ultimately, our goal is to ensure that clinicians are using the best available evidence to provide carefully considered, precise, and personalized treatment for every patient.” 

Fellow study co-author Dr. Morgan A Casal added, “A race-agnostic equation for evaluating kidney function that is at least as accurate as CKD-EPI would be ideal. Until such an equation is ready for widespread clinical implementation, physicians must take an individualized, patient-centered approach to evaluate kidney function when prescribing cancer pharmacotherapy.”

“That includes fully recognizing the limitations and implications of the various GFR-estimating equations, such as whether or not race is included, especially if the resulting choice or dosage of drug can have a substantial impact on survival,” Casal continued.

The authors conducted a retrospective analysis of 340 Black patients enrolled in phase 1 clinical trials at the National Cancer Institute from 1995 to 2010. The average age of patients was 57 years, and 172 were male while 168 were female.

Patients’ kidney function was estimated using the CKD-EPI equation with and without race as a factor. To compare, the authors also created estimated using the Cockcroft-Gault (CG) equation, which was developed in a primarily White cohort and does not take race into account.

The authors found that by excluding race, up to 5 percent and 18 percent of patients in the analysis would not be eligible for treatment or would receive lower dosage recommendations. The authors acknowledged that while the study only focused on Black cancer patients, likely other races would be impacted by the elimination of race as a variable.

To support health equality and eliminate racial and health disparities, providers should consider the complexities of how different races are impacted by certain types of chronic disease.