Alexion Rethinks Diversity Metrics And Why Race Alone Isn't Enough

By Adrian Kielhorn, senior director, head global HEOR neurology, Alexion, AstraZeneca Rare Disease

Clinical trials form the cornerstone of medical advancements and patient care. In the U.S., racial and ethnic minorities are often underrepresented in biomedical research, despite bearing a disproportionate burden of disease. In many diseases, like Alzheimer’s, the incidence is vastly higher in Black populations compared to other racial and ethnic groups, but clinical trials have traditionally included a disproportionate number of white participants. In fact, Black and Latino patients represent only about 20% of participants across all clinical trials.¹

This underrepresentation is even more pronounced in rare diseases. The inherently small patient populations make it challenging to achieve diversity due to the limited number of patients and geographical dispersion. Recruiting enough participants to show meaningful results is already hard — with some data suggesting that 86% of clinical trials fail to meet their recruitment targets² — and ensuring diverse representation adds another layer of complexity. These recruitment challenges mean that the process of translating lab research into potentially lifesaving treatments is often severely delayed.

The lack of diverse participation in clinical trials also can lead to an incomplete understanding of a disease's impact across different groups. Ensuring diverse representation in clinical trials for both common and rare diseases is crucial for developing therapies that are safe and effective, capturing the full spectrum of a disease's effects and treatment responses across different populations. 

However, the path to greater patient diversity is long and winding. Two factors play an important role here: 1) the history of systemic racism and 2) the lack of diversity measures.^3,4

The lack of diversity in clinical research needs to be addressed in light of a long history of systemic racism in the U.S. This has resulted in a greater allocation of resources toward facilitating white participation over that of other groups. The lack of diversity is the result of many visible and invisible barriers. Collecting more data on patients is an important first step in bringing these barriers to light.

In addition, we do not have a way to adequately measure diversity. The FDA uses questions on race and ethnicity that were developed as a standard for use in the U.S. census. The original purpose of the census was to capture who was white and who was not to determine access to certain societal privileges, not to measure diversity, though it is often used for that purpose today.⁵ If we are going to invest in greater trial diversity, we need measures that capture our progress. By expanding the scope of demographic data collection, we can enhance patient-trial matching and address barriers to participation more effectively.

Rethinking Demographic Metrics 

Conventional demographic metrics like age, sex, weight, race, and ethnicity fall short of capturing the true diversity of patient populations. To address these shortfalls, we must expand our efforts to gather data that encompasses the multifaceted nature of diverse patient populations. Racial and ethnic categories, often used as proxies for socioeconomic and cultural factors, offer a limited view. Shifting toward capturing cultural identity with greater nuance involves methodologies that allow for multiple choice responses or weighted percentages, providing a more authentic representation of trial participants. By doing so, we can enhance the inclusivity and accuracy of our research, leading to more effective and equitable healthcare solutions.

The FDA’s Role In Enhancing Diversity

The FDA’s Diversity Action Plan underscores the urgency of addressing this gap. It tackles the underrepresentation of minorities in clinical trials by enhancing recruitment strategies, fostering community partnerships, providing regulatory guidance, and emphasizing comprehensive data collection. It also promotes education for researchers and explores policy changes to ensure trials reflect diverse populations, ultimately aiming to improve medical advancements and patient care for all.

Additionally, the FDA has recommended strategies for increasing the inclusion of historically underrepresented racial and ethnic populations in clinical trials. These recommendations emphasize capturing additional factors that contribute to health disparities and differential access to healthcare, such as gender identity, socioeconomic status, disability, pregnancy and lactation status, and comorbidities. Expanding demographic data collection to include these factors will provide more accurate information on the diversity of clinical trial participants.

Insights From The Rethinking MeAsures of DivErsity (REMADE)

Alexion, AstraZeneca Rare Disease conducted the Rethinking MeAsures of DivErsity (REMADE) study to understand key elements of underrepresented populations’ ethnic, cultural, and socioeconomic identities that affect their engagement with the healthcare system. The study aimed to develop a questionnaire that expands patient baseline demographics captured in clinical trials.

Results from REMADE characterized several known barriers to healthcare access, including:

• affordability and access to healthcare: factors like income, household earnings, and health insurance coverage
• mobility: general mobility, disability, and transportation issues
• Personal disposition: employment status and caregiver responsibilities
• cultural identity: cultural identity, race, ethnicity, and skin tone

The study revealed that race and ethnicity are multidimensional. To accurately represent diversity in clinical trials, demographic characteristics must be expanded beyond traditional categories. The proposed questionnaire aims to capture not only racial and ethnic diversity but also other healthcare access determinants affecting clinical trial participation.

Capturing Comprehensive Diversity Data

The classification scheme commonly used in biomedical research includes five major groups: Black or African American, White, Asian, Native Hawaiian or other Pacific Islander, and American Indian or Alaska Native. This scheme is restrictive and often fails to capture the true diversity of underrepresented populations. Capturing cultural identity requires a new approach.

In the REMADE web survey, respondents could select multiple categories and assign weightings to race and ethnicity. This resulted in more diverse representation. For instance, while 96.2% of respondents selected either Black/African American or White under traditional measures, this number dropped to 44.7% when multiple categories and weightings were allowed. This suggests that singular categorical classification schemes do not adequately capture the racial and ethnic diversity of underrepresented people of color.

Race categories are based on social and political characteristics rather than biological ones, and they change over time and vary across societies. In the REMADE study, assessing skin tone instead of race provided a more accurate description of diversity. It also allows us to better measure the impact of colorism, discrimination on the basis of skin color, typically against those with darker skin. For example, among respondents who identified as 100% Black or African American, a wide range of skin tones were reported, highlighting the limitations of traditional racial categories.

Additionally, race has historically been used as a proxy for other important factors like household income, health insurance, and education level. Though deemed important, these remained unmeasured. The REMADE study captured these nuanced socioeconomic characteristics, revealing significant barriers to healthcare access among underrepresented populations. These barriers include low income, inadequate health insurance, and mobility issues, all of which limit access to information about, and participation in, clinical trials.

Progressing Toward More Inclusive Clinical Trials

The REMADE study underscores the importance of rethinking how we capture and understand diversity. By expanding demographic data collection to include cultural identity, socioeconomic status, and other access determinants, we can improve patient matching to trials and address participation barriers. In fact, as a result of this study, Alexion has modified its clinical trial protocol template to allow for the collection of these measures and is working toward including them in its clinical trials. Adoption of a comprehensive approach to demographic data collection will not only enhance the inclusivity of clinical trials by addressing barriers to participation but also ensure accurate representation of patients affected by a particular disease and, as a result, lead to more effective and equitable healthcare solutions.

References:

1. Cavazzoni P, et al. 2020 Drug Trials Snapshots Summary Report. U.S. FDA. 2021.
2. Huang GD, et al. Clinical Trials Recruitment Planning: A proposed framework from the Clinical Trials Transformation Initiative. Contemporary Clinical Trials. 2018;66:74-79. doi:10.1016/j.cct.2018.01.003 
3. Bailey ZD, et al. How structural racism works — racist policies as a root cause of U.S. racial health inequities. New England Journal of Medicine. 2021;384(8):768-773. doi:10.1056/nejmms2025396 
4. Sarfraz A. Understanding and promoting racial Diversity in Healthcare settings to address disparities in pandemic crisis management. Journal of Primary Care & Community Health. 2021;12: 1–7. 
5. Roman Y. The United States 2020 Census data: Implications for precision medicine and the research landscape. Per Med. 2022;19(1), 5–8. 

About The Author:

Adrian Kielhorn, Dipl.-Oek. has spent most of his career working for pharmaceutical companies in health economics and outcomes research (HEOR) roles. He broadened his experience working in market access, strategic pricing, marketing, and sales roles. As a leader, he instills in groups, teams, and organizations a passion for generating high-quality and patient-relevant value evidence that directly impacts market access. As a value evidence architect in rare diseases, he pioneers new approaches to measure value of pharmaceutical interventions. His interest in health equity has led him to develop diversity measures and identify barriers to improve access and treatments in rare diseases.