A Potential Role for Race in Medicine

Author

Matt Gynn | Queen's Medicine Class of 2022

Race and racism are two intertwined topics that have been brought to the forefront of medicine. It is important to acknowledge that there have been systemic biases for years in patient data collection. However, there are some unique circumstances where factoring in race may be appropriate for the foreseeable future. I present a few referenced examples that illustrate a potential role for race in medicine moving forward. I am by no means an expert, but I hope to shed light on reasons why to include and not include race in the context of our future patients. 

Why is race/ethnicity different than any other risk factor?

All medical information is not created equally. Incorrectly understanding the symptoms or treatments and a racial/ethnic correlation of a disease have very different outcomes. Mistakenly associating cough with streptococcal pharyngitis affects all patients on an even playing field. Incorrectly thinking about Black ancestry in the context of a gonorrheal infection may implicitly change your perception of the patient and/or the disease. As such, inappropriately thinking about Black ancestry does not affect all patients equally. These distinctions may not apply to every disease, but when race/ethnicity (or any demographic information) is listed as a risk factor, it’s important we critically analyze the actual evidence and utility of including it moving forward.

Arguments For Including Race - Example 1: Sickle Cell Disease

The primary argument for including race/ethnicity is its correlation with genetics. Genetics affect our health and set baseline probabilities for acquiring different diseases in our lifetimes. There are historical reasons as to why there are differences among ethnically diverse groups (which I won’t go into), but certain genetic variants are more common depending on your ancestry. Let’s use the example of sickle cell disease. In the U.S., the incidence of the sickle cell trait (one copy of the sickle cell hemoglobin variant) is 73.1 per 1,000 among Black newborns, 6.9 per 1,000 among Hispanic newborns, 2.2 per 1,000 among Asian, Native Hawaiian, or other Pacific Islander newborns, and 3.0 per 1,000 among White newborns[1]. So simply by having Black ancestry, the baseline probability of being born with sickle cell disease (two copies of the sickle cell hemoglobin variant) is roughly 1 in 365 whereas for Hispanic newborns it’s 1 in 16,300 (an almost 45x difference!)[1].

Unfortunately, we do not have rapid tests that can immediately sequence and interpret each patient’s genetic code. The big insights we have into our patient’s genetics are through their family history and, in a broader sense, their ancestry. Keep in mind that knowing one’s family history may be a luxury every patient might not have, so a patient’s race might be the only clue to any potential underlying genetic predispositions to specific diseases. 

However, maybe we should avoid the use of colour labels when referencing race/ethnicity. Using the sickle-cell example above, would it be more appropriate to use Sub-Saharan African ancestry in place of Black ancestry to remove the direct reference to skin colour?

Arguments Against Including Race - Example 2: COVID-19

The primary argument for excluding race is the inherent association with systemic racism and oppression. When we slap a race/ethnicity label on a disease, is it because there are real differences in the prevalence of genetic variations among different races? Or is it the product of an upstream chain of events that create inequality in our society? I want to present this quote from an article published in the very prestigious journal The Lancet on May 2nd, 2020. The title of the article is Ethnicity and COVID-19: an urgent public health research priority. ​

Ethnic classification systems have limitations but have been used to explore genetic and other population differences. Individuals from different ethnic backgrounds vary in behaviours, comorbidities, immune profiles, and risk of infection, as exemplified by the increased morbidity and mortality in black and minority ethnic (BME) communities in previous pandemics [2].

Consider the first descriptor used to describe why BME communities have increased morbidity and mortality: behaviours. This word places blame on the BME community and by including the word at the front of the list it implicitly suggests these “behaviours” are the most likely explanation for the differences in mortality and morbidity.  Essentially, this paragraph argues that these “[cultural] behaviours,” among other variables, warrant race/ethnicity being a risk factor for COVID-19 without the proper consideration for upstream variables that lead to differences in healthcare outcomes [2]. In another article published on May 7th, 2020 the data from the NHS in the UK is synthesized and the authors conclude:

People from Asian and black groups are at markedly increased risk of in-hospital death from COVID-19, and contrary to some prior speculation this is only partially attributable to pre-existing clinical risk factors or deprivation; further research into the drivers of this association is therefore urgently required [3].

Yet again, a 2020 article is ignoring the systemic issues and suggesting race is an appropriate risk factor for COVID-19.  Even in a meta-analysis of COVID patients published on June 3rd, 2020 Black patients are reported to have an increased risk of both infection and worse clinical outcomes [4]. I have been able to find a New England Journal of Medicine (NEJM) article that says there are no health disparities between White people and Black people once socioeconomic factors are adjusted for, however, these types of reports are in the minority [5]. 

COVID-19 highlights a problem with how clinicians like to collect data and publish. Medicine is very outcome-based; you take a cohort of patients and run advanced statistics to see what must explain the differences. I do not think this approach can adjust for systemic racism, but the “statistics say the differences are real” even after socioeconomic differences are adjusted for…  Furthermore, why are researchers so interested in determining which races are more susceptible to COVID-19? Race/ethnicity should not change how these patients are treated in the acute care setting. In this setting, patients should be worked up and investigated based on their symptom profile, not their race/ethnicity. Further, assuming race is the inciting factor rather than racism, systemic oppression, and flawed institutions limits our ability to tackle health inequities appropriately. 

By putting a label on BME communities very early in the COVID-19 pandemic, some clinicians will forever have their perceptions of the specific racial/ethnic communities altered. This label is unfair to these populations of patients and perpetuates systemic problems. Instead of starting at the outcome and working backwards, we should consider starting at the beginning (the genetics) and working forward before officially applying this label to any group of people. It’s more equitable to assume that the genetic variability among the ACE2 receptor (the receptor the COVID-19 virus binds to) is equal among all races [6]. If research can prove that a specific genetic variation is more prevalent in a defined population then perhaps it is appropriate to consider incorporating race/ethnicity in a relevant disease context.

Arguments For Including Race - Example 3: Cystic Fibrosis Mutations

Cystic fibrosis (CF) is a disease caused by mutations in the CFTR gene. It is more prevalent among the white population with a prevalence of ≈ 1 in 2500 among Ashkenazi Jewish and non-Hispanic White people, 1 in 15,000 among Black people, 1 in 35,000 among Asian people, and 1 in 10,900 among Native American people [7]. 

Even when disease is reported to be more common among the “majority”, it is important to still have some skepticism. Are these differences due to real genetic differences or better access to health care? In the case of CF, research has indeed specifically addressed this question and shown CF mutations are less common in minority populations [7]. 

Arguments Against Including Race - Example 4: HIV Infection Rates

In 1988, the NEJM published an article that stated HIV-seropositivity rates for patients attending STI clinics were higher among Black people than white people [8]. Again, I am no expert (and am open to learning more if I am incorrect), but I was not able to find any research that has shown a genetic variation of either the HLA receptors or CD4 receptors that increases the risk of HIV among the Black population. Certainly, if this research exists, it was not known in 1988. Yet the stigma and damage that was done by labelling being Black as a risk factor for an infectious disease is irreversible and unnecessary. 

Arguments For Including Race - Example 5: Warfarin Dosing

The inclusion of race in medicine should be under the pretenses that it can improve outcomes for our patients. So far, I have outlined mainly disease statistics that can be explained by the frequency of genetic variants in specific populations. These types of statistics are important in the framework of primary care when we want to either prevent disease or catch it as early as possible. What about acute care? Once there is a constellation of symptoms in front of us, is there any need to consider race? The assumptive answer to this question should always be no, but there are some instances where race can effectively guide treatment. 

In 2015, hematologists showed that ethnicity-based stratification of warfarin dosing improved dose prediction in both White and Black patients [9]. Warfarin is a drug with a very specific therapeutic window that must be monitored frequently, thus accurate dosing is important for the patient [10]. The explanation for these race-based differences is from previous studies that show different distributions of the gene variants related to warfarin’s metabolism between White and Black people [9].

Conclusion

I hope these examples highlight the importance of thinking about race with a critical lens moving forward. We can do unintentional damage by not thinking about race/ethnicity properly. If the reason race/ethnicity has historically been included can be traced back to systemic oppression, it should be excluded from medicine. At the same time, ignoring the unique circumstances where genetic differences are prevalent among specific ethnic groups also does our patients a disservice. 

There are many more examples of an inappropriate use of race in medicine published in this article by the NEJM for further reading.  ​

References

1. Ojodu, J., et al., Incidence of sickle cell trait--United States, 2010. MMWR. Morbidity and mortality weekly report, 2014. 63(49): p. 1155-1158.
2. Pareek, M., et al., Ethnicity and COVID-19: an urgent public health research priority. The Lancet, 2020. 395(10234): p. 1421-1422.
3. Williamson, E., et al., OpenSAFELY: factors associated with COVID-19-related hospital death in the linked electronic health records of 17 million adult NHS patients. medRxiv, 2020: p. 2020.05.06.20092999.
4. Pan, D., et al., The impact of ethnicity on clinical outcomes in COVID-19: A systematic review. EClinicalMedicine, 2020. 23: p. 100404.
5. Price-Haywood, E.G., et al., Hospitalization and Mortality among Black Patients and White Patients with Covid-19. New England Journal of Medicine, 2020. 382(26): p. 2534-2543.
6. Tai, W., et al., Characterization of the receptor-binding domain (RBD) of 2019 novel coronavirus: implication for development of RBD protein as a viral attachment inhibitor and vaccine. Cellular & Molecular Immunology, 2020. 17(6): p. 613-620.
7. Pique, L., et al., Cystic fibrosis newborn screening programs: implications of the CFTR variant spectrum in nonwhite patients. Genetics in Medicine, 2017. 19(1): p. 36-44.
8. Quinn, T.C., et al., Human Immunodeficiency Virus Infection among Patients Attending Clinics for Sexually Transmitted Diseases. New England Journal of Medicine, 1988. 318(4): p. 197-203.
9. Limdi, N.A., et al., Race influences warfarin dose changes associated with genetic factors. Blood, 2015. 126(4): p. 539-545.
10. Lenzini, P., et al., Integration of genetic, clinical, and INR data to refine warfarin dosing. Clinical pharmacology and therapeutics, 2010. 87(5): p. 572-578.