Putting Diversity at the Center of Clinical Trials With Real-World Data

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Robust data sets which can effectively represent diverse populations are key to driving greater inclusivity in trials.

Jen Lamppa, Associate Vice President, Clinical Analytics, Inovalon

Jen Lamppa, Associate Vice President, Clinical Analytics, Inovalon

In the realm of clinical research, a highly selective process prevails that favors patients with the financial and social means to participate. Often, inherent biases even influence who is invited to participate in clinical studies. Recent analysis outlines the stark disparities in the clinical study participation of diverse patient segments compared to a disease’s real-world disease demographics.Without diverse patient participation and data collection, clinical researchers are unable to robustly examine any underlying differences in new treatment safety and efficacy. As Nancy Krieger aptly states, “no data, no problem.”2

The evidence for expanding diversity and representation

As new treatments reach the market, a problem appears: real-world research shows dissatisfying outcomes and access disparities. One US study reveals that within the early years of a novel interventional device usage, women fare significantly worse than men, even after accounting for underlying differences.3 Real-world outcomes research aims to uncover and comprehend these biases, like a recent study demonstrating durable outcomes but limited use of CAR-T therapy in older patients.4 When underlying factors are removed from the equation, the possibility arises that these disparities are driven by inherent bias or patients’ underlying social determinants of health (SDOH).

For example, disparities between Black and White patients are evident. Our research has shown that Black patients with Advanced Parkinson’s Disease are 3x less likely to receive device-aided therapy than White patients.5 Black patients are not only less likely to receive interventions, but also experience worse overall outcomes compared to their White counterparts.6 There is a startling 41% greater breast cancer mortality likelihood for Black women compared to White women, with Black breast cancer patients experiencing the lowest 5-year survival rate of any race or ethnicity.7 To call on the other side of Nancy Krieger’s double-edged sword analogy, “problematic data, big problem.”2

The translation of these findings into actionable solutions and representative development-stage research has been disappointingly inadequate, often falling short of addressing the issue effectively. Though the profoundness of these findings is clear, understanding the “why” is far from straightforward and extends beyond medical care. It involves delving into underlying influencers of a patient’s health status with SDOH.

The cost of delaying diversity initiatives

As the patient impact of expanding diversity in clinical trials is increasingly clear, the potential costs of not accounting for SDOH are becoming more important to consider. Studies have uncovered some significant differences in healthcare resource utilization between different patient demographics.8 Another recent analysis found that hundreds of billions of dollars will be lost over the next 25 years among populations not proportionately represented in clinical trials.9

The analysis used the future elderly model (FEM) and looked at dollars lost based on shorter life expectancy, shortened disability-free lives, and fewer years working because of health disparities in underrepresented populations.

Additionally, costly delays in trials and mandatory post-market studies can be tied back to not factoring for appropriate representation. In trials that are completed, 60% have at least one substantial amendment—and 45% of those amendments could be avoided.9 In late-phase drug development, amendments cost $535,000.10 Finally, the number of FDA-approved drugs with racial or ethnic minority-specific post-marketing requirements grew 165% between 2019 and 2021, a significant price to pay for pivotal trials that do not account for all patients.11

The call for clear guidance

Recognizing the magnitude of this issue, the FDA has issued recent guidance encouraging better diversity and representation in clinical research.

However, at the recent FDA public workshop on diversity in clinical trials, prominent voices—including patients themselves—raised questions about how FDA guidance is evolving and the expected impact, especially when it lacks stated metrics to gauge its effectiveness. They advocated for improving the healthcare ecosystem to enable the clinical study participation of underrepresented patient populations experiencing real-world outcomes disparities.

Meanwhile, sponsors have taken steps towards better study diversity, but there is a noticeable gap between what's required and what's being done. Current goals are understated, with the life sciences industry believing they are making progress, even when meaningful and scalable action plans are lacking. Unlocking a solution that properly addresses the gaps in these initiatives requires a top-down approach that utilizes data and epidemiology coupled with a bottom-up approach implementing community and patient engagement.

Addressing disparities in clinical trials with real-world data

Harnessing the same real-world data that reveals outcomes disparities can help change the diversity narrative in clinical trials. Real-world data can be instrumental in identifying patient populations, characterizing their care networks, and making a compelling case for investment. However, care must be taken to ensure that the data has both the breadth and granularity of information required to avoid bias. A robust dataset to analyze real-world patient population demographics is ideal.

Sponsors and researchers have two main avenues for addressing these challenges.

The first is ensuring that actions are scalable, measurable, and impactful; that they are bold enough to drive real change and supported by data every step of the way. Diversity plans need to incorporate multiple meaningful data points to measure success from the national to the patient level in an integrated way.

The second option is leveraging data related to social determinants of health to drive change. This involves creating strong connections across the healthcare ecosystem to disseminate information effectively. Operationalizing this data allows for constructive conversations with healthcare providers, enabling them to understand and address the problem collectively. Additionally, the data can uncover diverse ways to engage with patients and make treatment more accessible.

Ultimately, recognizing the economic benefits of these initiatives is crucial, as aligning financial resources with the desire to effect positive change remains a challenge in the healthcare landscape. Sponsors and researchers should feel empowered to drive change in clinical research towards a more diverse future. They and their patients sit at the center of Krieger’s metaphor: “When it comes to health justice, the point of the two-edged sword of data is to produce actionable data for health equity and accountability.”2

Jen Lamppa, Associate Vice President, Clinical Analytics, Inovalon

References

  1. “Race/ethnicity reporting and representation in US clinical trials: A cohort study,” Brandon E. Turner, Jecca R. Steinberg, Brannon T. Weeks, Fatima Rodriguez, Mark R. Cullen, The Lancet Regional Health - Americas, Volume 11, 2022,100252, ISSN 2667-193X, https://doi.org/10.1016/j.lana.2022.100252
  2. “Talking With Nancy Krieger: Deconstructing Data for Health Equity,” Julia Haskins, de Beaumont, June 29, 2023, https://debeaumont.org/news/2023/talking-with-nancy-krieger-deconstructing-data-for-health-equity/
  3. “Sex Differences in Outcomes of Percutaneous Pulmonary Artery Thrombectomy in Patients With Pulmonary Embolism,” Manyoo A. Agarwal, MD, Jasmeet S. Dhaliwal, BS, Eric H. Yang, MD, John M. Moriarty, MD, Rajan Saggar, MD, Richard Channick, MD, CHEST Journal, August 1, 2022, https://journal.chestnet.org/article/S0012-3692(22)01351-4/pdf
  4. “Real-world experience of CAR T-cell therapy in older patients with relapsed/refractory diffuse large B-cell lymphoma,” Dai Chihara, Laura Liao, Joseph Tkacz, Anjali Franco, Benjamin Lewing, Karl M. Kilgore, Loretta J. Nastoupil, Lei Chen, American Society of Hematology, September 21, 2023, https://ashpublications.org/blood/article/142/12/1047/496474/Real-world-experience-of-CAR-T-cell-therapy-in
  5. “Impact of Social Determinants of Health on Access to Device Aided Therapy Services for Medicare Fee-for-Service Beneficiaries with Advanced Parkinson’s Disease,” Connie H. Yan, Alison R. Silverstein, Jill Schinkel, Christie Teigland, Inovalon, https://www.inovalon.com/publications/impact-of-social-determinants-of-health-on-access-to-device-aided-therapy-services-for-medicare-fee-for-service-beneficiaries-with-advanced-parkinsons-disease-3/
  6. “Racial and Socioeconomic Disparities in the Use and Outcomes of Endovascular Thrombectomy for Acute Ischemic Stroke,” A.M. Mehta, J.T. Fifi, H. Shoirah, T. Shigematsu, T.J. Oxley, C.P. Kellner, R.De Leacy, J. Mocco, and S. Majidi, AJNR, September 2021, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8423039/
  7. “What is a clinical trial?,” When We Tri(al), https://www.whenwetrial.org/why-trial/
  8. “Treatment Patterns and Healthcare Resource Utilization in Patients with Relapsed/Refractory Multiple Myeloma (RRMM) on Second and Third Line (2L/3L) Therapy, Classified By Urbanicity and Ethnicity,” Molinari A, Boytsov N, Tkacz J, Wang PF, Perera S, Norris K, Landi S, Gorsh B, ISPOR, May 2023, https://www.ispor.org/heor-resources/presentations-database/presentation/intl2023-3667/126891
  9. “Improving Representation in Clinical Trials and Research”, National Academies of Sciences, Engineering, and Medicine, 2022, https://nap.nationalacademies.org/catalog/26479/improving-representation-in-clinical-trials-and-research-building-research-equity
  10. “Common Clinical Trial Amendments, why they are submitted and how they can be avoided: a mixed methods study on NHS UK Sponsored Research (Amendments Assemble),” Joshi Shivam, Trials vol. 24,1 10. 4 Jan. 2023, doi:10.1186/s13063-022-06989-0, January 4, 2024, https://pubmed.ncbi.nlm.nih.gov/36600286/
  11. “U.S. Regulatory Landscape: Diversity in Clinical Trials,” TransCelerate BioPharma, 2022, https://www.transceleratebiopharmainc.com/wp-content/uploads/2022/03/TransCelerate-Regulatory-Landscape_Diversity.pdf
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