Robust data sets which can effectively represent diverse populations are key to driving greater inclusivity in trials.
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.1 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
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.
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
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.
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