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Annual Review of Medicine

Volume 74, 2023

Use of Race in Kidney Function Estimation: Lessons Learned and the Path Toward Health Justice

Abstract

In 2020, the nephrology community formally interrogated long-standing race-based clinical algorithms used in the field, including the kidney function estimation equations. A comprehensive understanding of the history of kidney function estimation and racial essentialism is necessary to understand underpinnings of the incorporation of a Black race coefficient into prior equations. We provide a review of this history, as well as the considerations used to develop race-free equations that are a guidepost for a more equity-oriented, scientifically rigorous future for kidney function estimation and other clinical algorithms and processes in which race may be embedded as a variable.

Keyword(s): clinical algorithms, equity, kidney function, kidney function estimation, race-based medicine
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/content/journals/10.1146/annurev-med-042921-124419
2023-01-27
2024-05-04
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Literature Cited

  1. 1.
    Cockwell P, Fisher L-A. 2020. The global burden of chronic kidney disease. Lancet 395:10225662–64
     [Google Scholar]
  2. 2.
    Crews DC, Liu Y, Boulware LE. 2014. Disparities in the burden, outcomes, and care of chronic kidney disease. Curr. Opin. Nephrol. Hypertens. 23:3298–305
     [Google Scholar]
  3. 3.
    Norton JM, Moxey-Mims MM, Eggers PW et al. 2016. Social determinants of racial disparities in CKD. J. Am. Soc. Nephrol. 27:92576–95
     [Google Scholar]
  4. 4.
    Bikbov B, Purcell CA, Levey AS et al. 2020. Global, regional, and national burden of chronic kidney disease, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet 395:10225709–33
     [Google Scholar]
  5. 5.
    Delgado C, Baweja M, Burrows NR et al. 2021. Reassessing the inclusion of race in diagnosing kidney diseases: an interim report from the NKF-ASN task force. Am. J. Kidney Dis. 78:1103–15
     [Google Scholar]
  6. 6.
    Delgado C, Baweja M, Crews DC et al. 2021. A unifying approach for GFR estimation: recommendations of the NKF-ASN task force on reassessing the inclusion of race in diagnosing kidney disease. J. Am. Soc. Nephrol. 32:122994–3015
     [Google Scholar]
  7. 7.
    Eneanya ND, Yang W, Reese PP 2019. Reconsidering the consequences of using race to estimate kidney function. JAMA 322:2113–14
     [Google Scholar]
  8. 8.
    Roberts D. 2011. Fatal Invention: How Science, Politics, and Big Business Re-Create Race in the Twenty-First Century New York: New Press/ORIM
  9. 9.
    Norris KC, Eneanya ND, Boulware LE. 2020. Removal of race from estimates of kidney function: first, do no harm. JAMA 325:2135–37
     [Google Scholar]
  10. 10.
    Mohottige D, Diamantidis CJ, Norris KC, Boulware LE. 2021. Racism and kidney health: turning equity into a reality. Am. J. Kidney Dis. 77:6951–62
     [Google Scholar]
  11. 11.
    Eneanya ND, Boulware LE, Tsai J et al. 2022. Health inequities and the inappropriate use of race in nephrology. Nat. Rev. Nephrol. 18:284–94
     [Google Scholar]
  12. 12.
    Hsu C-Y, Bansal N. 2011. Measured GFR as “gold standard”—all that glitters is not gold?. Clin. J. Am. Soc. Nephrol. 6:81813
     [Google Scholar]
  13. 13.
    Molitoris BA, Reilly ES. 2016. Quantifying glomerular filtration rates in acute kidney injury: a requirement for translational success. Semin. Nephrol. 36:131–41
     [Google Scholar]
  14. 14.
    Mohottige D, Lunn MR. 2020. Ensuring gender-affirming care in nephrology: improving care for transgender and gender-expansive individuals. Clin. J. Am. Soc. Nephrol. 15:81195–97
     [Google Scholar]
  15. 15.
    Delanaye P, Cavalier E, Pottel H. 2017. Serum creatinine: not so simple. ! Nephron 136:4302–8
     [Google Scholar]
  16. 16.
    Mohottige D, Tuot DS. 2022. Advancing kidney health equity: influences of gender-affirming hormone therapy on kidney function. Clin. J. Am. Soc. Nephrol. 17:1281–83
     [Google Scholar]
  17. 17.
    Levey AS, Inker LA, Coresh J. 2014. GFR estimation: from physiology to public health. Am. J. Kidney Dis. 63:5820–34
     [Google Scholar]
  18. 18.
    Cockcroft DW, Gault MH. 1976. Prediction of creatinine clearance from serum creatinine. Nephron 16:131–41
     [Google Scholar]
  19. 19.
    Effersoe P. 1957. Relationship between endogenous 24-hour creatinine clearance and serum creatinine concentration in patients with chronic renal disease. Acta Med. Scand. 156:6429–34
     [Google Scholar]
  20. 20.
    Jelliffe RW. 1973. Letter: Creatinine clearance: bedside estimate. Ann. Intern. Med. 79:4604–5
     [Google Scholar]
  21. 21.
    Siersbaek-Nielsen K, Hansen JM, Kampmann J, Kristensen M. 1971. Rapid evaluation of creatinine clearance. Lancet 7709:1133–34
     [Google Scholar]
  22. 22.
    Levey AS, Bosch JP, Lewis JB et al. 1999. A more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction equation. Ann. Intern. Med. 130:6461–70
     [Google Scholar]
  23. 23.
    Casal MA, Nolin TD, Beumer JH. 2019. Estimation of kidney function in oncology. Clin. J. Am. Soc. Nephrol. 14:4587–95
     [Google Scholar]
  24. 24.
    Morris H, Mohan S 2020. Using race in the estimation of glomerular filtration rates: time for a reversal?. Curr. Opin. Nephrol. Hypertens. 29:2227–31
     [Google Scholar]
  25. 25.
    Jones CA, McQuillan GM, Kusek JW et al. 1998. Serum creatinine levels in the US population: third National Health and Nutrition Examination Survey. Am. J. Kidney Dis. 32:6992–99
     [Google Scholar]
  26. 26.
    Grubbs V. 2020. Precision in GFR reporting: Let's stop playing the race card. Clin. J. Am. Soc. Nephrol. 15:81201–2
     [Google Scholar]
  27. 27.
    Worrall JG, Phongsathorn V, Hooper RJL, Paice EW. 1990. Racial variation in serum creatine kinase unrelated to lean body mass. Rheumatology 29:5371–73
     [Google Scholar]
  28. 28.
    Harsha DW, Frerichs RR, Berenson GS. 1978. Densitometry and anthropometry of black and white children. Hum. Biol. 50:3261–80
     [Google Scholar]
  29. 29.
    Levey AS, Coresh J, Greene T et al. 2006. Using standardized serum creatinine values in the Modification of Diet in Renal Disease Study equation for estimating glomerular filtration rate. Ann. Intern. Med. 145:4247–54
     [Google Scholar]
  30. 30.
    Delanaye P, Ebert N, Melsom T et al. 2016. Iohexol plasma clearance for measuring glomerular filtration rate in clinical practice and research: a review. Part 1: How to measure glomerular filtration rate with iohexol?. Clin. Kidney J. 9:5682–99
     [Google Scholar]
  31. 31.
    Earley A, Miskulin D, Lamb EJ et al. 2012. Estimating equations for glomerular filtration rate in the era of creatinine standardization: a systematic review. Ann. Intern. Med. 156:11785–95
     [Google Scholar]
  32. 32.
    Levey AS, Stevens LA, Schmid CH et al. 2009. A new equation to estimate glomerular filtration rate. Ann. Intern. Med. 150:9604–12
     [Google Scholar]
  33. 33.
    Stevens LA, Schmid CH, Greene T et al. 2010. Comparative performance of the CKD epidemiology collaboration (CKD-EPI) and the modification of diet in renal disease (MDRD) study equations for estimating GFR levels above 60 mL/min/1.73 m2. Am. J. Kidney Dis. 56:3486–95
     [Google Scholar]
  34. 34.
    Hsu C-Y, Yang W, Parikh RV et al. 2021. Race, genetic ancestry, and estimating kidney function in CKD. N. Engl. J. Med. 385:191750–60
     [Google Scholar]
  35. 35.
    Olabisi Opeyemi A, Zhang J-Y, VerPlank L et al. 2016. APOL1 kidney disease risk variants cause cytotoxicity by depleting cellular potassium and inducing stress-activated protein kinases. PNAS 113:4830–37
     [Google Scholar]
  36. 36.
    Pollak MR, Friedman DJ. 2020. The genetic architecture of kidney disease. Clin. J. Am. Soc. Nephrol. 15:2268–75
     [Google Scholar]
  37. 37.
    Witzig R. 1996. The medicalization of race: scientific legitimization of a flawed social construct. Ann. Intern. Med. 125:8675–79
     [Google Scholar]
  38. 38.
    Wailoo K, Nelson A, Lee C 2012. Genetics and the Unsettled Past: The Collision of DNA, Race, and History New Brunswick, NJ: Rutgers Univ. Press
  39. 39.
    Léonard MdN. 2014. Census and racial categorization in France: invisible categories and color-blind politics. Humanity Soc. 38:167–88
     [Google Scholar]
  40. 40.
    Delanaye P, Mariat C, Maillard N et al. 2011. Are the creatinine-based equations accurate to estimate glomerular filtration rate in African American populations?. Clin. J. Am. Soc. Nephrol. 6:4906–12
     [Google Scholar]
  41. 41.
    Stevens LA, Coresh J, Schmid CH et al. 2008. Estimating GFR using serum cystatin C alone and in combination with serum creatinine: a pooled analysis of 3,418 individuals with CKD. Am. J. Kidney Dis. 51:3395–406
     [Google Scholar]
  42. 42.
    Tangri N, Stevens LA, Schmid CH et al. 2011. Changes in dietary protein intake has no effect on serum cystatin C levels independent of the glomerular filtration rate. Kidney Int. 79:4471–77
     [Google Scholar]
  43. 43.
    Shlipak MG, Sarnak MJ, Katz R et al. 2005. Cystatin C and the risk of death and cardiovascular events among elderly persons. N. Engl. J. Med. 352:202049–60
     [Google Scholar]
  44. 44.
    Inker LA, Schmid CH, Tighiouart H et al. 2012. Estimating glomerular filtration rate from serum creatinine and cystatin C. N. Engl. J. Med. 367:120–29
     [Google Scholar]
  45. 45.
    Inker LA, Astor BC, Fox CH et al. 2014. KDOQI US commentary on the 2012 KDIGO clinical practice guideline for the evaluation and management of CKD. Am. J. Kidney Dis. 63:5713–35
     [Google Scholar]
  46. 46.
    Stevens LA, Claybon MA, Schmid CH et al. 2011. Evaluation of the Chronic Kidney Disease Epidemiology Collaboration equation for estimating the glomerular filtration rate in multiple ethnicities. Kidney Int. 79:5555–62
     [Google Scholar]
  47. 47.
    Matsuo S, Imai E, Horio M et al. 2009. Revised equations for estimated GFR from serum creatinine in Japan. Am. J. Kidney Dis. 53:6982–92
     [Google Scholar]
  48. 48.
    Horio M, Imai E, Yasuda Y et al. 2010. Modification of the CKD epidemiology collaboration (CKD-EPI) equation for Japanese: accuracy and use for population estimates. Am. J. Kidney Dis. 56:132–38
     [Google Scholar]
  49. 49.
    Ma YC, Zuo L, Chen JH et al. 2006. Modified glomerular filtration rate estimating equation for Chinese patients with chronic kidney disease. J. Am. Soc. Nephrol. 17:102937–44
     [Google Scholar]
  50. 50.
    van Deventer HE, George JA, Paiker JE et al. 2008. Estimating glomerular filtration rate in black South Africans by use of the modification of diet in renal disease and Cockcroft-Gault equations. Clin. Chem. 54:71197–202
     [Google Scholar]
  51. 51.
    Madala ND, Nkwanyana N, Dubula T, Naiker IP. 2012. Predictive performance of eGFR equations in South Africans of African and Indian ancestry compared with ⁹⁹mTc-DTPA imaging. Int. Urol. Nephrol. 44:3847–55
     [Google Scholar]
  52. 52.
    Eastwood JB, Kerry SM, Plange-Rhule J et al. 2010. Assessment of GFR by four methods in adults in Ashanti, Ghana: the need for an eGFR equation for lean African populations. Nephrol. Dial. Transpl. 25:72178–87
     [Google Scholar]
  53. 53.
    Jessani S, Levey AS, Bux R et al. 2014. Estimation of GFR in South Asians: a study from the general population in Pakistan. Am. J. Kidney Dis. 63:149–58
     [Google Scholar]
  54. 54.
    Kumar V, Yadav AK, Yasuda Y et al. 2018. Existing creatinine-based equations overestimate glomerular filtration rate in Indians. BMC Nephrol. 19:122
     [Google Scholar]
  55. 55.
    Rocha AD, Garcia S, Santos AB et al. 2020. No race-ethnicity adjustment in CKD-EPI equations is required for estimating glomerular filtration rate in the Brazilian population. Int. J. Nephrol. 2020:2141038
     [Google Scholar]
  56. 56.
    de Brito Barcellos RC, de Matos JPS, Kang HC et al. 2015. Comparison of serum creatinine levels in different color/race categories in a Brazilian population. Cadernos Saude Publica 31:1565–69
     [Google Scholar]
  57. 57.
    Teo BW, Koh YY, Toh QC et al. 2014. Performance of the CKD-EPI creatinine-cystatin C glomerular filtration rate estimation equations in a multiethnic Asian population. Singapore Med. J. 55:12656–59
     [Google Scholar]
  58. 58.
    Flamant M, Vidal-Petiot E, Metzger M et al. 2013. Performance of GFR estimating equations in African Europeans: basis for a lower race-ethnicity factor than in African Americans. Am. J. Kidney Dis. 62:1182–84
     [Google Scholar]
  59. 59.
    Gama RM, Clery A, Griffiths K et al. 2021. Estimated glomerular filtration rate equations in people of self-reported black ethnicity in the United Kingdom: inappropriate adjustment for ethnicity may lead to reduced access to care. PLOS ONE 16:8e0255869
     [Google Scholar]
  60. 60.
    Mohottige D, Diamantidis CJ, Norris KC, Boulware LE. 2021. Time to repair the effects of racism on kidney health inequity. Am. J. Kidney Dis. 77:6951–62
     [Google Scholar]
  61. 61.
    Am. Soc. Nephrol., Natl. Kidney Found 2021. Removing race from estimates of kidney function: a joint statement from the presidents of the American Society of Nephrology and the National Kidney Foundation Press Release, Mar. 9. https://www.asn-online.org/about/press/releases/ASN_PR_20210309_Press_release_NKF_A.pdf
  62. 62.
    1947. Sickle cell anemia, a race specific disease. JAMA 133:133–34
     [Google Scholar]
  63. 63.
    Cerdeña JP, Plaisime MV, Tsai J. 2020. From race-based to race-conscious medicine: how anti-racist uprisings call us to act. Lancet 396:102571125–28
     [Google Scholar]
  64. 64.
    Braun L, Wentz A, Baker R et al. 2020. Racialized algorithms for kidney function: erasing social experience. Soc. Sci. Med. 2020:113548
     [Google Scholar]
  65. 65.
    Hirschfeld LA. 1998. Natural assumptions: race, essence, and taxonomies of human kinds. Soc. Res. 65:2331–49
     [Google Scholar]
  66. 66.
    Williams DR, Collins C. 2001. Racial residential segregation: a fundamental cause of racial disparities in health. Public Health Rep 116:5404–16
     [Google Scholar]
  67. 67.
    Boyd RW, Lindo EG, Weeks LD et al. 2020. On racism: a new standard for publishing on racial health inequities. Health Aff. Forefront Blog Jul. 2. https://www.healthaffairs.org/do/10.1377/forefront.20200630.939347/full/
    [Google Scholar]
  68. 68.
    Krieger N. 2016. Living and dying at the crossroads: racism, embodiment, and why theory is essential for a public health of consequence. Am. J. Public Health 106:5832–33
     [Google Scholar]
  69. 69.
    Kuzawa CW, Sweet E. 2009. Epigenetics and the embodiment of race: developmental origins of US racial disparities in cardiovascular health. Am. J. Hum. Biol. 21:12–15
     [Google Scholar]
  70. 70.
    Udler MS, Nadkarni GN, Belbin G et al. 2015. Effect of genetic African ancestry on eGFR and kidney disease. J. Am. Soc. Nephrol. 26:71682–92
     [Google Scholar]
  71. 71.
    Ross LF, Thistlethwaite JR Jr. 2016. Introducing genetic tests with uncertain implications in living donor kidney transplantation: ApoL1 as a case study. Prog. Transpl. 26:3203–6
     [Google Scholar]
  72. 72.
    Royal CD, Novembre J, Fullerton SM et al. 2010. Inferring genetic ancestry: opportunities, challenges, and implications. Am. J. Hum. Genet. 86:5661–73
     [Google Scholar]
  73. 73.
    Via M, Ziv E, Burchard EG. 2009. Recent advances of genetic ancestry testing in biomedical research and direct to consumer testing. Clin. Genet. 76:3225–35
     [Google Scholar]
  74. 74.
    Fujimura JH, Rajagopalan R. 2011. Different differences: the use of ‘genetic ancestry’ versus race in biomedical human genetic research. Soc. Stud. Sci. 41:15–30
     [Google Scholar]
  75. 75.
    Tishkoff SA, Kidd KK. 2004. Implications of biogeography of human populations for ‘race’ and medicine. Nat. Genet. 36:11S21–27
     [Google Scholar]
  76. 76.
    Duster T. 2003. Backdoor to Eugenics. Routledge UK: Psychology Press
     [Google Scholar]
  77. 77.
    Grubbs V, Cerdeña JP, Non AL. 2022. The misuse of race in the search for disease-causing alleles. Lancet 399:103301110–11
     [Google Scholar]
  78. 78.
    Mohottige D, Boulware LE, Ford CL et al. 2022. Use of race in kidney research and medicine. Clin. J. Am. Soc. Nephrol. 17:2314–22
     [Google Scholar]
  79. 79.
    Soylu Yalcinkaya N, Estrada-Villalta S, Adams G 2017. The (biological or cultural) essence of essentialism: implications for policy support among dominant and subordinated groups. Front. Psychol. 8:900
     [Google Scholar]
  80. 80.
    Gelman SA, Hirschfeld LA. 1999. How biological is essentialism?. Folkbiology 9:403–46
     [Google Scholar]
  81. 81.
    Osborne NG, Feit MD. 1992. The use of race in medical research. JAMA 267:2275–79
     [Google Scholar]
  82. 82.
    Ford CL, Airhihenbuwa CO. 2010. Critical race theory, race equity, and public health: toward antiracism praxis. Am. J. Public Health 100:Suppl. 1S30–35
     [Google Scholar]
  83. 83.
    Shin J-I, Sang Y, Chang AR et al. 2020. The FDA metformin label change and racial and sex disparities in metformin prescription among patients with CKD. J. Am. Soc. Nephrol. 31:81847–58
     [Google Scholar]
  84. 84.
    Levey AS, Titan SM, Powe NR et al. 2020. Kidney disease, race, and GFR estimation. Clin. J. Am. Soc. Nephrol. 15:81203–12
     [Google Scholar]
  85. 85.
    Powe NR. 2020. Black kidney function matters: use or misuse of race?. JAMA 324:8737–38
     [Google Scholar]
  86. 86.
    Purnell TS, Bae S, Luo X et al. 2020. National trends in the association of race and ethnicity with predialysis nephrology care in the United States from 2005 to 2015. JAMA Netw. Open 3:8e2015003
     [Google Scholar]
  87. 87.
    Barrett TM, Davenport CA, Ephraim PL et al. 2022. Disparities in discussions about kidney replacement therapy in CKD care. Kidney360 3:1158–63
     [Google Scholar]
  88. 88.
    Mehrotra R, Soohoo M, Rivara MB et al. 2016. Racial and ethnic disparities in use of and outcomes with home dialysis in the United States. J. Am. Soc. Nephrol. 27:72123–34
     [Google Scholar]
  89. 89.
    Purnell TS, Crews DC. 2019. Persistent disparities in preemptive kidney transplantation. Clin. J. Am. Soc. Nephrol. 14:101430–31
     [Google Scholar]
  90. 90.
    Purnell TS, Luo X, Cooper LA et al. 2018. Association of race and ethnicity with live donor kidney transplantation in the United States from 1995 to 2014. JAMA 319:149–61
     [Google Scholar]
  91. 91.
    Ahmed S, Nutt CT, Eneanya ND et al. 2020. Examining the potential impact of race multiplier utilization in estimated glomerular filtration rate calculation on African-American care outcomes. J. Gen. Intern. Med. 36:464–71
     [Google Scholar]
  92. 92.
    Bragg-Gresham J, Zhang X, Le D et al. 2021. Prevalence of chronic kidney disease among black individuals in the US after removal of the black race coefficient from a glomerular filtration rate estimating equation. JAMA Netw. Open 4:1e2035636
     [Google Scholar]
  93. 93.
    Tsai JW, Cerdeña JP, Goedel WC et al. 2021. Evaluating the impact and rationale of race-specific estimations of kidney function: estimations from U.S. NHANES, 2015–2018. eClinicalMedicine 42:1–7
     [Google Scholar]
  94. 94.
    Yap E, Prysyazhnyuk Y, Ouyang J et al. 2021. The implication of dropping race from the MDRD equation to estimate GFR in an African American-only cohort. Int. J. Nephrol. 2021:1880499
     [Google Scholar]
  95. 95.
    Diao JA, Wu GJ, Taylor HA et al. 2020. Clinical implications of removing race from estimates of kidney function. JAMA 325:2184–86
     [Google Scholar]
  96. 96.
    Chu CD, Powe NR, Crews DC, Tuot DS. 2021. CKD progression from the time of estimated GFR-based waitlist eligibility and racial disparities in transplant access. Am. J. Kidney Dis. 79:6841–48
     [Google Scholar]
  97. 97.
    Ku E, McCulloch CE, Adey DB et al. 2021. Racial disparities in eligibility for preemptive waitlisting for kidney transplantation and modification of eGFR thresholds to equalize waitlist time. J. Am. Soc. Nephrol. 32:3677–85
     [Google Scholar]
  98. 98.
    Zelnick LR, Leca N, Young B, Bansal N 2020. Estimation of glomerular filtration rate with versus without the race coefficient and time to eligibility for kidney transplant. JAMA Netw. Open 4:1e2034004
     [Google Scholar]
  99. 99.
    Glassock RJ, Warnock DG, Delanaye P. 2017. The global burden of chronic kidney disease: estimates, variability and pitfalls. Nat. Rev. Nephrol. 13:2104–14
     [Google Scholar]
  100. 100.
    Guess TJ. 2006. The social construction of whiteness: racism by intent, racism by consequence. Crit. Sociol. 32:4649–73
     [Google Scholar]
  101. 101.
    Inker LA, Eneanya ND, Coresh J et al. 2021. New creatinine- and cystatin C–based equations to estimate GFR without race. N. Engl. J. Med. 385:191737–49
     [Google Scholar]
/content/journals/10.1146/annurev-med-042921-124419
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Use of Race in Kidney Function Estimation: Lessons Learned and the Path Toward Health Justice
Annual Review of Medicine 74, 385 (2023); https://doi.org/10.1146/annurev-med-042921-124419
/content/journals/10.1146/annurev-med-042921-124419
/content/journals/10.1146/annurev-med-042921-124419
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