Demographic clinical trial diversity assessment methods: Use of real-world data

Diversity in clinical trials is defined by the inclusion of clinical trial participants from various demographic groups that are representative of the broader population impacted by a disease state. Diversity in clinical trials is critical in identifying potential differences in safety and efficacy of treatments across races, ethnicities, ages, sexes, or other variables. In the United States, clinical trial diversity is often benchmarked against US Census data, which may limit the representativeness of patient demographics in clinical trials. Disease-specific, demographic estimates from real-world data (RWD) can facilitate benchmarking of clinical trials, support trial enrollment and the development of trial diversity plans. Notably, development and dissemination of these estimates from RWD can be challenging without a standardized process. To address this issue, we developed a new evaluation framework to assess patient demographics and characteristics within specific disease populations using RWD and disease population estimates. Suitable databases were identified using predefined criteria such as accessibility to patient-level data, availability of all demographic variables of interest, sufficient sample size of the disease population, and availability of population weights to enhance generalizability. Concurrent data were gathered via targeted literature reviews for each disease condition. Together, this data was used to create disease-specific, demographic estimate profiles to inform diverse enrollment goals for prospective clinical trials. We present two examples of application of this framework to illustrate the results in the case of two disease states, rheumatoid arthritis and stroke.

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Publication Details

Journal
Contemporary Clinical Trials Communications
Published
2025-01-10
DOI
https://doi.org/10.1016/j.conctc.2025.101432
Primary Topic
Health Systems, Economic Evaluations, Quality of Life
Type
article
Field-Weighted Citation Impact
0.00

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article

Demographic clinical trial diversity assessment methods: Use of real-world data

Hua Chen, Nnadozie Emechebe, Leon Raskin, Wendy Sebby et al.
Contemporary Clinical Trials Communications
Health Systems, Economic Evaluations, Quality of Life
article

Demographic clinical trial diversity assessment methods: Use of real-world data

Hua Chen, Nnadozie Emechebe, Leon Raskin, Wendy Sebby, Ning Cheng, Kim Ribeiro, S. M. Crawford, Sudeep Karve, Jailene Leal
article en

Abstract

Diversity in clinical trials is defined by the inclusion of clinical trial participants from various demographic groups that are representative of the broader population impacted by a disease state. Diversity in clinical trials is critical in identifying potential differences in safety and efficacy of treatments across races, ethnicities, ages, sexes, or other variables. In the United States, clinical trial diversity is often benchmarked against US Census data, which may limit the representativeness of patient demographics in clinical trials. Disease-specific, demographic estimates from real-world data (RWD) can facilitate benchmarking of clinical trials, support trial enrollment and the development of trial diversity plans. Notably, development and dissemination of these estimates from RWD can be challenging without a standardized process. To address this issue, we developed a new evaluation framework to assess patient demographics and characteristics within specific disease populations using RWD and disease population estimates. Suitable databases were identified using predefined criteria such as accessibility to patient-level data, availability of all demographic variables of interest, sufficient sample size of the disease population, and availability of population weights to enhance generalizability. Concurrent data were gathered via targeted literature reviews for each disease condition. Together, this data was used to create disease-specific, demographic estimate profiles to inform diverse enrollment goals for prospective clinical trials. We present two examples of application of this framework to illustrate the results in the case of two disease states, rheumatoid arthritis and stroke.

Contemporary Clinical Trials CommunicationsVol. 44
AbbVie (United States) (US), University of Houston (US)
AbbVie
Openalex Percentile: Top 99%
Health Systems, Economic Evaluations, Quality of Life
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