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Race adjustment

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In the United States, there are several race-based calculations and medical decision making tools that physicians use to decide treatments for various conditions, including chronic kidney disease and asthma.[1] These formulas have been documented to result in the denial of certain resources and treatment options to Black patients that are available to white patients.[2]

History

Both globally and in the United States, there have been significant differences in Western-based medical treatment according to racial identification. These biases have changed over time, but have deep roots in both Western medical practices and social theory.

Racially-biased discourse was pervasive in the development of Western medical thought. Carl Linnaeus, a Swedish physician, labeled five varieties of the human species by their physiognomic characteristics.[3] He included characteristics such as hair type and skin thickness, but also relative characteristics relating to greed, honor, and laziness.[3] These characteristics, though not scientifically sound, cemented European racial superiority and embedded wide-spread myths that still affect Western medical thought.

Charles White. an English physician and surgeon, further believed that different races were aligned on a "Great Chain of Being".[4] His beliefs espoused different origins for different races, claiming that white and black people were different species entirely.[4] While others, such as French naturalist Georges-Louis Leclerc and German anatomist Johann Blumenbach believed all races came from a single origin point, but that the races degenerated over time to form distinct differences based on environmental factors.[5] Others like Thomas Jefferson believed that there was obvious racial inferiority between white and Black persons, calling on science to explore it further.[6] While Charles Darwin believed in the basic equality of the human species, his ideas were adapted by social theorists like Francis Galton who coined the term eugenics in his book Inquiries into Human Faculty and Its Development published in 1883.

Influence of Slavery and Eugenics on Medical Practice

Perceived differences in origin were used as an excuse for slavery throughout the United States, and this belief impacted medical treatment and experimentation on Black persons in the United States.[7] Medical treatment of Black persons in the United States came into specific focus after 1808, after a federal ban on slave imports was implemented.[8] Physicians such as J Marion Sims started to focus on the existing Black population, attempting to observe and use Black slaves for medical reasons.[9][8] Some of these treatments and experiments were for the broader medical community, others were to increase birth rates and therefore domestic slave populations. Sims, for instance, the father of modern gynecology, performed surgery on twelve women in the 1840s from his backyard in Montgomery, Alabama.[10] All of the women were enslaved.[10] As modern medical science grew, it developed in conjunction with notions of racism, derived from both experiments and societal sentiments. These factors embedded a sense of racial difference and inequity that persists today. In the modern United States, for instance, Black women are sometimes three to four times more likely to die from issues during pregnancy compared to white women.[8]

Experimentation was wide-spread among medical students and professionals alike. In the 19th century, many American medical schools used Black bodies stolen through grave robbing for dissection and medical experimentation.[11] This thought process of viewing Black bodies and persons, alive or dead, as an "other", ripe for experimentation, persisted well into the Jim Crow era. For instance, the Tuskegee Experiment, initiated in 1932 and ending in 1972, infected Black men with syphilis against their knowledge, leading to over 100 deaths.[12]

This experimentation went hand in hand with a legacy of colonialism. Colonies served as ample testing grounds for medical advancements by European and North American medical professionals.[13][14] Honor Smith, a British physician at Oxford University, was jovial about the opportunity to test on colonial populations; in 1955, he stated, “[I]t is the almost unlimited field that Africa offers for clinical research that I find so enthralling…problems of the first interest abound, [and] clinical material is unlimited."[15]

These experiments coincided with developments in anthropology and theory around race, with many prevalent thinkers of the time believing there to be distinct differences, even distinct origins between different races.[6] After World War II, scientific racism and eugenics began to be dismissed at large by the scientific community. While certain experiments and explicitly eugenicist thought continued, many of the theories surrounding racial difference and eugenic superiority were discredited and pushed out of the mainstream.[16] Certain medical practices such as equations and decision-making tools continued with these biases in mind. As the internet developed, diagnostic tools were often based on decision-making tools embedded with a perceived racial difference.[17] In the 21st century, these tools and methods have come under more scrutiny.[17]

Modern Changes in Perspective

Over the past few decades as our understanding of race and ethnicity has evolved, advocates for change have been questioning the assumptions that numerous medical decision making tools and formulas are based upon.

In recent years, students, petitions and social media campaigns have recently been at the forefront for driving medical institutions to change the way they utilize certain clinical decision making tools such as eGFR calculations.[18] In 2017, Beth Israel eliminated the race factor in calculating kidney function.[19] In May 2020, through medical student advocacy to their administration, the University of Washington transitioned to a new eGFR calculation that excludes race as a variable.[20]

"Race correction" variables in clinical medicine

Nephrology

The estimated glomerular filtration rate (eGFR) is supposed to give doctors a sense of how well the kidneys are working as they separate out waste from the body. Algorithms often differ between racial groups in the United States, with Black patients receiving generally higher eGFR values than their white counterparts.[21] The eGFR remains the standard across the United States, with professionals citing higher serum creatinine concentrations among Black patients compared to white patients.[22][23] Reasons for this assumption vary, but it is thought to partially stem from the notion that Black persons are more muscular.[22] This idea has come under more and more scrutiny, with certain institutions choosing to deviate from the race-adjusted model as a result.[24] These biases have sometimes delayed or complicated medical care, a factor that exacerbates already higher rates of death kidney failure among Black persons compared to the overall population.

Kidney transplants also have racial implications, both direct and indirect. The Kidney Donor Risk Index (KDRI), the United State’s official kidney allocation index, was developed in 2014.[25] Race is among the factors used to predict the success of a kidney graft, with Black donors’ kidneys often thought to perform worse than kidneys from other donors.[26] Being Black results in a demarcation as a less preferable donor by the KDRI.[27] This creates a snowball effect, with less kidneys from Black donors in the system. In turn, Black patients in need of kidney donations are affected. Black patients already face longer wait times than patients of other races in need of kidney transplants. Black patients are more likely to receive a kidney transplant from a Black donor, according to recent studies.[27] This lack of resources can exacerbate the already lengthy wait times. In recent years, some professionals have called attention to these disparities, advocating to replace “the vagaries associated with inclusion of a variable termed ‘race’.”[26]

Obstetrics

In the United States, African American and Hispanic women continue to have higher rates of cesarean section than do white women in the US.[28] Medical decision making formulas such as the Vaginal Birth after Cesarean (VBAC) algorithm have been found to contribute to such disparities for women of color. The VBAC is used to estimate success rates for vaginal birth among expectant mothers with histories of previous cesarean delivery and is used by clinicians to counsel whether to offer trials of labor or repeat cesarean section.[29] There are two race-based correction factors incorporated in the formula, one for African American women and one for Hispanic women. These factors are subtracted from the likelihood of having a successful vaginal birth after Cesarean and thus inherently predict a lower risk of vaginal birth success for African American and Hispanic individuals.[30] These lower estimates may discourage health providers from offering trials of vaginal labor to expectant women of color, although the health benefits of vaginal birth (lower rates of surgical complication, faster recovery, fewer complication in later pregnancies) have been well documented.[1] These race/ethnicity associations have been challenged by health providers since they have not been thoroughly supported by biology and are concerning as black women have higher rates of maternal mortality.[31]

Pulmonology

Spirometers are devices that measure lung volume and airflow. They are used for the diagnosis and monitoring of several respiratory diseases such as asthma and chronic obstructive pulmonary disease (COPD).[32] In the United States, spirometers use “correction factors” for individuals labelled as Black (10-15%) or Asian (4-6%).[1] There have been several concerns about equity in these lung function formulas including the misdiagnosis of disease severity in asthma and COPD.[33] Recent interest in investigating the basis for why these correction factors came to be spawned a systematic review of 226 articles published between 1922 and 2008 that found that less than one in five studies defined race and that researchers frequently assumed inherent or genetic differences.[34]

See also

References

  1. ^ a b c Vyas, Darshali A.; Eisenstein, Leo G.; Jones, David S. (2020-08-27). "Hidden in Plain Sight — Reconsidering the Use of Race Correction in Clinical Algorithms". New England Journal of Medicine. 383 (9): 874–882. doi:10.1056/NEJMms2004740. ISSN 0028-4793.
  2. ^ Obermeyer, Ziad; Powers, Brian; Vogeli, Christine; Mullainathan, Sendhil (2019-10-25). "Dissecting racial bias in an algorithm used to manage the health of populations". Science. 366 (6464): 447–453. doi:10.1126/science.aax2342. ISSN 0036-8075. PMID 31649194.
  3. ^ a b Linné, Carl von (1767). Caroli a Linné ... Systema naturae,: per regna tria naturae, secundum classes, ordines, genera, species, cum characteribus, differentiis, synonymis, locis (in Latin). Typis Ioannis Thomae.
  4. ^ a b Jackson, John P.; Weidman, Nadine M. (2004). Race, Racism, and Science: Social Impact and Interaction. ABC-CLIO. ISBN 978-1-85109-448-6.
  5. ^ Harris, Marvin (2001-08-14). The Rise of Anthropological Theory: A History of Theories of Culture. AltaMira Press. ISBN 978-0-7591-1699-3.
  6. ^ a b Garrod, Joel Z. (January 2006). "A Brave Old World: An Analysis of Scientific Racism and BiDil®". McGill Journal of Medicine. 9 (1): 54–60. ISSN 1201-026X. PMC 2687899. PMID 19529811.
  7. ^ Alexander Thomas and Samuell Sillen (1972). Racism and Psychiatry. New York: Carol Publishing Group.
  8. ^ a b c Bachynski, Kathleen. "Perspective | American medicine was built on the backs of slaves. And it still affects how doctors treat patients today". Washington Post. ISSN 0190-8286. Retrieved 2020-10-17.
  9. ^ "J. Marion Sims, MD: Why He and His Accomplishments Need to Continue to be Recognized a Commentary and Historical Review". Journal of the National Medical Association. 111 (4): 436–446. 2019-08-01. doi:10.1016/j.jnma.2019.02.002. ISSN 0027-9684.
  10. ^ a b Kapsalis, Terri (2002). "Mastering the Female Pelvis: Race and the Tools of Reproduction". In Wallace-Sanders, Kimberly (ed.). Skin Deep, Spirit Strong: The Black Female Body in American Culture (PDF). Ann Arbor, MI: University of Michigan Press. pp. 263–300. ISBN 978-0472067077.
  11. ^ Meier, Allison C. (2018-08-24). "Grave Robbing, Black Cemeteries, and the American Medical School". JSTOR Daily. Retrieved 2020-10-17.
  12. ^ "Tuskegee Study - Timeline - CDC - NCHHSTP". www.cdc.gov. 2020-07-16. Retrieved 2020-10-17.
  13. ^ Tilley, Helen (2016-07-01). "Medicine, Empires, and Ethics in Colonial Africa". AMA Journal of Ethics. 18 (7): 743–753. doi:10.1001/journalofethics.2016.18.7.mhst1-1607. ISSN 2376-6980.
  14. ^ Tilley, Helen (2011-04-15). Africa as a Living Laboratory: Empire, Development, and the Problem of Scientific Knowledge, 1870-1950. University of Chicago Press. ISBN 978-0-226-80348-7.
  15. ^ Smith, Honor (1955-01-01). "Medicine in Africa as I have seen It". African Affairs. 54 (214): 28–36. doi:10.1093/oxfordjournals.afraf.a094264. ISSN 0001-9909.
  16. ^ Kevles, Daniel J. (1985). In the Name of Eugenics: Genetics and the Uses of Human Heredity. Harvard University Press. ISBN 9780674445574.
  17. ^ a b Kolata, Gina (2020-07-21). "Many Medical Decision Tools Disadvantage Black Patients". The New York Times. ISSN 0362-4331. Retrieved 2020-10-17.
  18. ^ "Push to remove racist bias from kidney testing gains new ground". STAT. 2020-07-17. Retrieved 2020-10-17.
  19. ^ Kolata, Gina (2020-07-21). "Many Medical Decision Tools Disadvantage Black Patients". The New York Times. ISSN 0362-4331. Retrieved 2020-10-17.
  20. ^ "UW Medicine to exclude race from calculation of eGFR (measure of kidney function) | Department of Medicine | University of Washington". medicine.uw.edu. Retrieved 2020-10-17.
  21. ^ Levey, Andrew S.; Stevens, Lesley A.; Schmid, Christopher H.; Zhang, Yaping (Lucy); Castro, Alejandro F.; Feldman, Harold I.; Kusek, John W.; Eggers, Paul; Van Lente, Frederick; Greene, Tom; Coresh, Josef (2009-05-05). "A New Equation to Estimate Glomerular Filtration Rate". Annals of internal medicine. 150 (9): 604–612. ISSN 0003-4819. PMC 2763564. PMID 19414839.
  22. ^ a b Eneanya, Nwamaka Denise; Yang, Wei; Reese, Peter Philip (2019-07-09). "Reconsidering the Consequences of Using Race to Estimate Kidney Function". JAMA. 322 (2): 113. doi:10.1001/jama.2019.5774. ISSN 0098-7484.
  23. ^ Levey, Andrew S.; Tighiouart, Hocine; Titan, Silvia M.; Inker, Lesley A. (2020-05-01). "Estimation of Glomerular Filtration Rate With vs Without Including Patient Race". JAMA Internal Medicine. 180 (5): 793–795. doi:10.1001/jamainternmed.2020.0045. ISSN 2168-6106.
  24. ^ Hsu, Joy; Johansen, Kirsten L.; Hsu, Chi-yuan; Kaysen, George A.; Chertow, Glenn M. (2008-07-01). "Higher Serum Creatinine Concentrations in Black Patients with Chronic Kidney Disease: Beyond Nutritional Status and Body Composition". Clinical Journal of the American Society of Nephrology. 3 (4): 992–997. doi:10.2215/CJN.00090108. ISSN 1555-9041. PMID 18417750.
  25. ^ Rao, Panduranga S.; Schaubel, Douglas E.; Guidinger, Mary K.; Andreoni, Kenneth A.; Wolfe, Robert A.; Merion, Robert M.; Port, Friedrich K.; Sung, Randall S. (2009-07-27). "A Comprehensive Risk Quantification Score for Deceased Donor Kidneys: The Kidney Donor Risk Index". Transplantation. 88 (2): 231–236. doi:10.1097/TP.0b013e3181ac620b. ISSN 0041-1337.
  26. ^ a b Julian, B. A.; Gaston, R. S.; Brown, W. M.; Reeves‐Daniel, A. M.; Israni, A. K.; Schladt, D. P.; Pastan, S. O.; Mohan, S.; Freedman, B. I.; Divers, J. (2017). "Effect of Replacing Race With Apolipoprotein L1 Genotype in Calculation of Kidney Donor Risk Index". American Journal of Transplantation. 17 (6): 1540–1548. doi:10.1111/ajt.14113. ISSN 1600-6143. PMC 5429996. PMID 27862962.
  27. ^ a b Cannon, R. M.; Brock, G. N.; Marvin, M. R.; Slakey, D. P.; Buell, J. F. (2012). "The Contribution of Donor Quality to Differential Graft Survival in African American and Caucasian Renal Transplant Recipients". American Journal of Transplantation. 12 (7): 1776–1783. doi:10.1111/j.1600-6143.2012.04091.x. ISSN 1600-6143.
  28. ^ Curtin, Sally C.; Kozak, Lola Jean (December 1998). "Decline in U.S. Cesarean Delivery Rate Appears to Stall". Birth. 25 (4): 259–262. doi:10.1046/j.1523-536x.1998.00259.x. ISSN 0730-7659.
  29. ^ mfmunetwork.bsc.gwu.edu https://mfmunetwork.bsc.gwu.edu/PublicBSC/MFMU/VGBirthCalc/vagbirth.html. Retrieved 2020-10-17. {{cite web}}: Missing or empty |title= (help)
  30. ^ Grobman, William A.; Lai, Yinglei; Landon, Mark B.; Spong, Catherine Y.; Leveno, Kenneth J.; Rouse, Dwight J.; Varner, Michael W.; Moawad, Atef H.; Caritis, Steve N.; Harper, Margaret; Wapner, Ronald J. (April 2007). "Development of a Nomogram for Prediction of Vaginal Birth After Cesarean Delivery". Obstetrics & Gynecology. 109 (4): 806–812. doi:10.1097/01.aog.0000259312.36053.02. ISSN 0029-7844.
  31. ^ Vyas, Darshali A.; Jones, David S.; Meadows, Audra R.; Diouf, Khady; Nour, Nawal M.; Schantz-Dunn, Julianna (May 2019). "Challenging the Use of Race in the Vaginal Birth after Cesarean Section Calculator". Women's Health Issues. 29 (3): 201–204. doi:10.1016/j.whi.2019.04.007. ISSN 1049-3867.
  32. ^ Burney, P.; Jarvis, D.; Perez-Padilla, R. (January 2015). "The global burden of chronic respiratory disease in adults". The International Journal of Tuberculosis and Lung Disease: The Official Journal of the International Union Against Tuberculosis and Lung Disease. 19 (1): 10–20. doi:10.5588/ijtld.14.0446. ISSN 1815-7920. PMID 25519785.
  33. ^ Kumar, Rajesh; Seibold, Max A.; Aldrich, Melinda C.; Williams, L. Keoki; Reiner, Alex P.; Colangelo, Laura; Galanter, Joshua; Gignoux, Christopher; Hu, Donglei; Sen, Saunak; Choudhry, Shweta (2010-07-22). "Genetic Ancestry in Lung-Function Predictions". New England Journal of Medicine. 363 (4): 321–330. doi:10.1056/NEJMoa0907897. ISSN 0028-4793. PMC 2922981. PMID 20647190.
  34. ^ Braun, Lundy; Wolfgang, Melanie; Dickersin, Kay (2013-06-01). "Defining race/ethnicity and explaining difference in research studies on lung function". European Respiratory Journal. 41 (6): 1362–1370. doi:10.1183/09031936.00091612. ISSN 0903-1936. PMID 22878881.
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