Volume 38 Number 3 | June 2024

Sara A. Taylor, PhD, MLS(ASCP)CMMBCM, ASCLS Diversity Advocacy Council Counselor-at-Large

Letycia C. Nuñez Argote, PhD, CPH, MLS(ASCP)CM, ASCLS Diversity Advocacy Council Past Chair

Sara TaylorLetycia Nunez ArgoteClinical laboratory data and clinical research are used together to enhance health outcomes. The clinical laboratory generates test results that help clinicians diagnose, monitor, and treat diseases. Clinical researchers use this data to understand disease mechanisms, validate hypotheses, develop new therapies, and to evaluate treatment response. Accurate and timely clinical data contribute to evidence-based decision making, thus clinical research often begins with clinical laboratory results. Moreover, when research ideas move into formal clinical trials, laboratory testing is essential, as researchers rely on lab results to validate hypotheses, assess treatment effects, and monitor patient progress. But how can clinical data contribute to or mitigate disparities in healthcare and research?

Many studies have found that there are significant demographic disparities in clinical trials, with consistent underrepresentation due to sex, age, racial or ethnic background, health status, and geographic location.1,2 While statistics vary according to the aim of the trial, generally people who identify as white comprise 57.8 percent of the U.S. population, but they make up 68 percent of clinical trial participation, an overrepresentation of +17.6 percent. In contrast, individuals who identify as black and Hispanic/Latinx comprise 12.1 percent and 18.7 percent of the U.S. population, yet these groups are underrepresented in clinical trials by -34 percent and -41 percent respectively. Asian individuals are the only racial group whose inclusion in clinical trials closely aligns with their percentage of the U.S. population.1,2 Moreover, the inclusion of males over females predominates in an abundance of clinical trials, as does the propensity to exclude the elderly.3,4

The tendency to bias results in favor of younger, white males in clinical trials lowers the efficacy of the study and can produce undesirable outcomes in underrepresented groups. This is hardly a sound scientific approach, since all groups are likely to be the recipients of the treatments tested in clinical trials. People from groups that are historically underrepresented in research (HUIR) have different genetic, environmental, and social factors that affect the risk, progression, and treatment response to many therapeutics. Therefore, it is important to increase the diversity and inclusion of all people to better access the impact of testing and treatments under investigation.

There have been some official steps taken toward encouraging a transition to more inclusive clinical research practices. On April 13, 2022, the Food and Drug Administration (FDA) issued formal guidance for sponsors involved in the development of medical therapeutics with a Race and Ethnicity Diversity Plan. This initiative requires sponsors to submit a formal plan to the FDA as part of their request for FDA approval. The plan is designed to assist in the development of strategies to enroll more participants from HUIR populations into clinical trials.2 The FDA plan recommends several strategies such as: 1) the development of specific eligibility criteria for each trial, which should require researchers to justify why some individuals may not be included; 2) the minimization of restrictive criteria, such as excluding participants who have co-morbidities such as an active or previous cancer diagnosis, or infection with certain pathologies such as HBV or HIV; and 3) reduction of barriers that might limit participation such as participant mistrust, language/cultural constraints, health literacy, and participation that creates a significant burden for enrollees.

“People from groups that are historically underrepresented in research (HUIR) have different genetic, environmental, and social factors that affect the risk, progression, and treatment response to many therapeutics. Therefore, it is important to increase the diversity and inclusion of all people to better access the impact of testing and treatments under investigation.”

In addition to FDA mandates, the National Institutes of Health (NIH) has implemented the Inclusion Across the Lifespan policy to promote the inclusion of older adults in clinical research.5 Moreover, the NIH has a Policy and Guidelines on Inclusion of Women and Minorities directive that requires applications for NIH funding involving human subjects to address the inclusion of women, minorities, and children in the proposed research. Phase III clinical trials must be conducted and reported by stratifying sex/gender and race/ethnicity outcomes.5 Finally, 42 USC 289a-2 is a provision within the United States Code that requires the director of the NIH to ensure that HUIR groups are included in all research proposals.6 Unfortunately, these proposals and regulations do not guarantee that clinical trials will accurately represent appropriate numbers of HUIR individuals, therefore it is important for clinical laboratory professionals to be mindful of these changes, and to work towards reducing the exclusion of HUIR groups in clinical trials.

There are barriers that hinder robust inclusion of HUIR groups in clinical trials to consider. An initial barrier to participation in clinical trials is simply public awareness of upcoming clinical trials. Partnering with community-based organizations, soliciting the support of community leaders, tailoring marketing campaigns (e.g., using social media), and organizing educational events are all ways we can engage HUIR groups. If your institution is participating in a sponsored clinical trial, make sure to spread the word to help increase participation of HUIR individuals.

Developing richer data sets can also reduce the exclusion of HUIR groups from clinical trials. Recently a new term has been coined to describe the integration of clinical laboratory data and artificial intelligence—clinlabomics.7 Using clinical laboratory generated test results, clinlabomics is used to analyze laboratory data to establish a relationship between test results and diagnosis/treatment. Because of the large amount of data that is collected in these settings, predictive models of diagnosis, risk stratification, and prognosis can be developed.8 Clinlabomics is still in its infancy, but it is reasonable to predict that richer data sets will help trial organizers devise strategies to increase participation of HUIR in clinical trials. As the people populating the results that are feeding these algorithms, our profession should advocate for data that is inclusive and equitable.

Additionally, people who belong to HUIR groups can be encouraged to embrace the worthiness of the research inquiry. Clinical laboratory tests are of value only if they are valid, and if they lead to improved patient outcomes. Ideally, the data collected in a clinical trial will be applied in clinical practice. Educational campaigns that emphasize the value of robust community participation, endorsement by professional organizations, and support of trial participation by community leaders and community groups can all be encouraged by laboratory professionals.

And finally, active participation in a clinical trial may be hindered by logistical constraints. Prospective participants may have difficulty with transportation, costs associated with participation, and limits on time available for participation in a research study. In this digital age, the use of technology in the form of decentralized clinical trials (DCTs) should be investigated as a means of reducing these types of operational constraints.8 The FDA defines DCTs as “clinical trials executed through telemedicine and mobile/local healthcare providers, using processes and technologies that differ from the traditional clinical trial model.”8

When DCTs are used, part or all of the trial takes place in locations other than the primary study site. Rather than study participants traveling to a central study site, they can enroll, consent, and be monitored in locales that are convenient for them—often from their homes. Technologies such as computers, smartphones, tablets, and wearables are utilized to elicit study participation. If not, all data collection is supported with DCTs, a hybrid system might be able to be employed.

In summary, participation of HUIR populations in clinical trials remains a concern. However, there are straightforward practices that can be used by clinical professionals and clinical trial organizers working collaboratively to address this critical issue. As FDA Commissioner Robert M. Califf, MD, eloquently states, “The U.S. population has become increasingly diverse, and ensuring meaningful representation of racial and ethnic minorities in clinical trials for regulated medical products is fundamental to public health.”

References
  1. Jensen E, Jones N, Rabe M, et al. 2020 U.S. Population More Racially, Ethnically Diverse Than in 2010. U.S. Census Bureau. August 12, 2021. Accessed February 21, 2024. https://www.census.gov/library/stories/2021/08/2020-united-states-population-more-racially-ethnically-diverse-than-2010.html
  2. Adashi EY, & Cohen IG. The FDA initiative to assure racial and ethnic diversity in clinical trials. The Journal of the American Board of Family Medicine. 2023; 36(2):366-368.
  3. Florisson S, Aagesen EK, Bertelsen AS, Nielsen LP, & Rosholm JU. (2021). Are older adults insufficiently included in clinical trials?—An umbrella review. Basic & Clinical Pharmacology & Toxicology. 2021; 128(2):213-223.
  4. Babcook MA, Nidhi N, Carter RR., et al. Representation of women in clinical trials supporting the FDA-approval of contemporary anticancer therapies. Journal of Clinical Oncology. 2022; 40(16_suppl):6521-6521.
  5. Hunold KM, Goldberg EM, Caterino JM., et al. Inclusion of older adults in emergency department clinical research: strategies to achieve a critical goal. Academic Emergency Medicine. 2022; 29(3):376-383.
  6. Inclusion of women and minorities in clinical research. 42 U.S.C. §289a-2(2020).
  7. Wen X, Leng P, Wan J, et al. Clinlabomics: leveraging clinical laboratory data by data mining strategies. BMC bioinformatics. 2022; 23(1); 387.
  8. Apostolaros M, Babaian D, Corneli A, et al. Legal, regulatory, and practical issues to consider when adopting decentralized clinical trials: recommendations from the clinical trials transformation initiative. Therapeutic innovation & regulatory science. 2020; 54:779-787.

Sara A. Taylor is Assistant Professor at University of North Carolina-Chapel Hill, Division of Clinical Laboratory Science, in Chapel Hill, North Carolina.

Letycia C. Nuñez Argote is Clinical Associate Professor at the University of Kansas Medical Center in Kansas City, Kansas.