(B-191) Setting diversity goals for clinical trials: Epidemiologic considerations

Background: Ensuring diversity in clinical trials (CTs) has been emphasized by ICH and FDA. In its 2024 guidance, FDA required sponsors to set CT enrollment goals by race, ethnicity (R/E), sex and age, to improve enrollment of historically underrepresented populations. Diversity enrollment goals are informed by real-world (RW) prevalence estimates, disease epidemiology, treatment patterns and disparities in the intended use population (IUP).

Objectives: To provide an overview of the epidemiologic considerations in setting diversity goals for CTs.

Methods: A 3-step approach is presented for setting diversity goals: 1. Obtaining real-world data (RWD) on the IUP, 2. Interpreting the RW distributions and 3. Setting evidence-based and feasible diversity goals. Epidemiologic considerations at each step are discussed using a case study of a CT on prostate cancer (PC).

Results: Obtaining RWD: epidemiologic considerations in this step include RWD source representativeness of the IUP, and completeness and accuracy of coding for R/E and age. For example, Surveillance, Epidemiology and End Results program (SEER) is a more appropriate source compared to National Cancer Database (NCDB) given it is more representative and specifically designed to capture R/E minorities, despite having a lower sample size. Additionally, it is important to consider period effects and long-term epidemiologic trends. PC incidence has been declining over the past 10 years while mortality has remained unchanged; thus, a 10-year period prevalence would not accurately reflect current PC distributions. It is also important to identify clinically- and epidemiologically- relevant subgroups for diversity planning (e.g., pregnancy, lactation, socioeconomic status). In PC, age is of particular importance as evidenced by higher incidence and worse outcomes in those aged ≥ 65.
Interpreting the data: prevalence estimates may not always be a true reflection of the RW distributions. It is important that they are interpreted in the context of information and selection biases at play. In PC, systemic under-screening/treatment of Black and Hispanic patients may contribute to underestimation of RW prevalence of PC in these groups. Other factors include differential misdiagnosis or under/mis-coding in historically under-represented populations.
Setting goals: Epidemiologic data and evidence should be considered to decide if diversity goals should be set higher than the observed prevalence estimates (e.g., when one group is at higher risk of adverse outcomes from the drug), or lower (e.g. when study eligibility criteria may differentially impact the enrollment of one group).

Conclusions: It is important to apply epidemiologic knowledge to obtain, interpret, and triangulate RWD to inform diversity goals.