Abstract: TH-PO840
Modeling Diversity in Diabetic Kidney Disease Clinical Trials Using Real-World Data
Session Information
- Race, Ethnicity, and Gender in Kidney Health and Care
October 24, 2024 | Location: Exhibit Hall, Convention Center
Abstract Time: 10:00 AM - 12:00 PM
Category: Diversity and Equity in Kidney Health
- 900 Diversity and Equity in Kidney Health
Authors
- Bevan, Andrew M., PPD, Part of Thermo Fisher Scientific, Cambridge, United Kingdom
- Garrisi, Davide, PPD, Part of Thermo Fisher Scientific, Milan, Italy
- Stump, Sarah Dixon, PPD, Part of Thermo Fisher Scientific, Wilmington, North Carolina, United States
- Angeles, Carmichael, PPD, Part of Thermo Fisher Scientific, Wilmington, North Carolina, United States
Background
The FDA places emphasis on studying clinically relevant trial populations but does not address how to define these. The authors previously reported underrepresentation of people of African descent in lupus nephritis trials, but this has not been investigated in more common renal disorders such as diabetic kidney disease (DKD). The study aims to compare demographics of individuals with DKD from a large electronic health record (EHR) database with completed US-only DKD trials and propose statistical parameters for cohort sizes to support DKD trial planning.
Methods
Data was obtained from the TriNetX Analytics Network containing EHRs from >150 million individuals in the US. Demographics (gender, race, ethnicity) were assessed for those with an ICD-10-CM code E11.22 Type 2 Diabetes Mellitus with DKD in the last 5 years that did not also have an ICD-10-CM code N18.6 ESRD. Binomial confidence intervals were calculated to define demographic cohort sample sizes for clinical trials. Data were compared to average proportions of demographic cohorts in completed US-only DKD trials reported in clinicaltrials.gov.
Results
Real-world Data: 583,660 individuals met eligibility, gender distribution (50.2% Male, 45.4% Female, 4.4% Unknown), race distribution (62.8% White, 19.8% Black or African American, 4.0% Asian, 13.4% Other/Unknown), ethnic distribution (73.5% Non-Hispanic or Latino, 6.9% Hispanic or Latino, 19.6% Unknown).
Clinical Trials: 9 DKD clinical trials were evaluated (956 subjects). Gender was reported for 9 trials (Male 64.8%, Female 35.2%). Race was reported for 6 trials (813 subjects), 77.4.% White, 18.2% Black or African American, 2.0% Asian, 2.3% Other/Unknown. Ethnicity was reported for 3 trials (549 subjects), 64.4.% Non-Hispanic/Latino, 35.6% Hispanic/Latino.
Cohort Modelling: Based on an analysis of binomial confidence intervals, a US DKD trial of 100 subjects would be considered statistically representative (p < 0.05) of the TriNetX population if it included a range of 40-60 Male, 35-55 Female, 53-72 White, 13-29 Black or African American and 13-29 Hispanic/Latino patients.
Conclusion
Our data shows underrepresentation of non-white and female patients in US-only DKD trials compared to the TriNetX DKD population. Large EHR databases are one method to determine “real-world” demographics to support the planning of “representative” trial cohorts.