Regulatory Science Virtual Symposium: “Study Design for Clinical Trials: Types and Trends” Session 3: Gender, Race, and Ethnicity in Clinical Trials (2023)

1. Objectives
   1. National Institute of Health (NIH), U.S. Food and Drug Administration (FDA) policies on inclusion and reporting by sex, race, ethnicity
   2. Rationale for inclusion and reporting by sex, race ethnicity
   3. Examples of heterogeneity of intervention effects by sex
   4. Implications for trial design and reporting
2. NIH Policies on Inclusion
   1. Must provide justification if clinical trial does not include both women and men
   2. If prior research suggests that there might be differences in intervention effects by sex, race, and ethnicity, then the trial should be designed to test efficacy within relevant subgroups
3. FDA Policies
   1. All NIH applications must consider the inclusion of women, minorities, and children
   2. Example of FDA Guidance: Collection of Race and Ethnicity Data in Clinical Trials
   3. Standardized and consistent collection and reporting of sex, race, and ethnicity data
   4. Expected to enroll participants by age, sex, race, and ethnicity that reflect the demographics of the clinical condition under study
   5. Be sure to include plans for retention and recruitment for specific subgroups
   6. Two-Question Format
      1. Question 1: Do you consider yourself Hispanic/Latino or not Hispanic/Latino?
      2. Question 2: Which of the following five racial designations best describes you? More than one choice is acceptable.
4. NIH and FDA policies are recommendations, not mandates
5. Rationale
   1. Incidence and survival of many diseases as well as drug effects vary by sex, race, and ethnicity
   2. Disparities are related to genetic differences, lifestyle, environment, and socioeconomic factors
   3. Variable drug effects on persons based on sex, race, ethnicity (and age)
   4. Clinical trial participation is historically highly educated white participants
   5. Reduction of health disparities requires that all demographic groups be represented in clinical trials
   6. Inclusion of sub-groups needs to start with the early phases of the study
6. Subgroup Reporting
   1. FDA demographic rule: Submission of safety and efficacy data by age, sex, and age
   2. Population-level PK studies
7. Sex and Clinical Trials
   1. Studies were historically limited to men because women can become pregnant; hormonal fluctuations; effects on drug metabolism; and perceptions that certain illnesses are “male” diseases; women typically are smaller than men
8. Sex vs. Gender in Clinical Trials
   1. Sex is biological vs. gender is socially constructed
   2. Clinical trials often use these terms interchangeably
   3. More current guidelines encourage differentiation
9. Sex and Gender in Clinical Trials
   1. Both factors influence how/what particular treatment a person selects, how they adhere to it, and how they metabolize a drug
   2. Ideally, trials should include equal numbers of men and women, because the total sample analysis may mask sex/gender differences in efficacy or safety; in cholesterol-lowering treatments, there were differences between the two groups
10. Race (Mis)reporting and Participation in Cancer Clinical Trials
    1. Looked at cancer clinical trials for drug approvals from 2008-2018
    2. 145 trials reported only on one race, and 18 only reported on 4 groups (White, Asian, Black, and Hispanic)
11. Other Examples of Race/Ethnic Differences in Clinical Trials
    1. Race-focused trials showed that heart failure, kidney disease, and hypertension differ between Black and White populations
12. COVID-19 and Vaccine Trials
    1. COVID-19 disproportionately affected racial and ethnic minorities
13. Implications for Trial Design and Analyses
    1. To address and understand health disparities, clinical trials must enroll enough participants in these subgroups to look for differences in efficacy, safety, and pathophysiology
    2. Reporting results by these sub-groups will assist in the analysis of data and identification of differences after the trials have ended
    3. Previous studies have recruited homogeneous groups to reduce statistical variability, but it is important to this also reduces the generalizability of research to other groups
    4. Groups that would be treated by this medical intervention should be the ones participating in the research studies
    5. Important to identify and respond to recruitment and retention
       1. Use community-based diverse stakeholders to advise and assist with trial
       2. Moving clinical trials out of institutions and into communities
       3. Having minority patients engage with professionals of similar backgrounds
       4. Multi-site trials
       5. Use of technology in clinical trial design
14. Subgroup Statistical Analyses
    1. If a known gender/race/ethnicity effect of intervention exists, then trial design must have a sufficient sample size to conduct valid statistical analyses within each relevant group.
    2. If unknown, the sufficient sample size in subgroups remain necessary to obtain reasonably precise estimates of effects
    3. Statistical models will include a product interaction term (e.g., treatment x gender) to formally test for subgroup difference in effects
15. Thank you!

Accompanying text created by Roxy Terteryan, RKS Project Administrator, SC CTSI (atertery@usc.edu) and Cyan Tan, Student Worker