A framework for setting enrollment goals to ensure participant diversity in sponsored clinical trials in the United States.


Journal

Contemporary clinical trials
ISSN: 1559-2030
Titre abrégé: Contemp Clin Trials
Pays: United States
ID NLM: 101242342

Informations de publication

Date de publication:
06 2023
Historique:
received: 12 12 2022
revised: 06 04 2023
accepted: 10 04 2023
medline: 29 5 2023
pubmed: 14 4 2023
entrez: 13 4 2023
Statut: ppublish

Résumé

Diversity in clinical trials (CTs) has the potential to improve health equity and close health disparities. Underrepresentation of historically underserved groups compromises the generalizability of trial findings to the target population, hinders innovation, and contributes to low accrual. The aim of this study was to establish a transparent and reproducible process for setting trial diversity enrollment goals informed by the disease epidemiology. An advisory board of epidemiologists with expertise in health disparities, equity, diversity, and social determinants of health was convened to evaluate and strengthen the initial goal-setting framework. Data sources used were the epidemiologic literature, US Census, and real-world data (RWD); limitations were considered and addressed where appropriate. A framework was designed to safeguard against the underrepresentation of historically medically underserved groups. A stepwise approach was created with Y/N decisions based on empirical data. We compared race and ethnicity distributions in the RWD of six diseases from Pfizer's portfolio chosen to represent different therapeutic areas (multiple myeloma, fungal infections, Crohn's disease, Gaucher disease, COVID-19, and Lyme disease) to the distributions in the US Census and established trial enrollment goals. Enrollment goals for potential CTs were based on RWD for multiple myeloma, Gaucher disease, and COVID-19; enrollment goals were based on the Census for fungal infections, Crohn's disease, and Lyme disease. We developed a transparent and reproducible framework for setting CT diversity enrollment goals. We note how limitations due to data sources can be mitigated and consider several ethical decisions in setting equitable enrollment goals.

Sections du résumé

BACKGROUND
Diversity in clinical trials (CTs) has the potential to improve health equity and close health disparities. Underrepresentation of historically underserved groups compromises the generalizability of trial findings to the target population, hinders innovation, and contributes to low accrual. The aim of this study was to establish a transparent and reproducible process for setting trial diversity enrollment goals informed by the disease epidemiology.
METHOD
An advisory board of epidemiologists with expertise in health disparities, equity, diversity, and social determinants of health was convened to evaluate and strengthen the initial goal-setting framework. Data sources used were the epidemiologic literature, US Census, and real-world data (RWD); limitations were considered and addressed where appropriate. A framework was designed to safeguard against the underrepresentation of historically medically underserved groups. A stepwise approach was created with Y/N decisions based on empirical data.
RESULTS
We compared race and ethnicity distributions in the RWD of six diseases from Pfizer's portfolio chosen to represent different therapeutic areas (multiple myeloma, fungal infections, Crohn's disease, Gaucher disease, COVID-19, and Lyme disease) to the distributions in the US Census and established trial enrollment goals. Enrollment goals for potential CTs were based on RWD for multiple myeloma, Gaucher disease, and COVID-19; enrollment goals were based on the Census for fungal infections, Crohn's disease, and Lyme disease.
CONCLUSIONS
We developed a transparent and reproducible framework for setting CT diversity enrollment goals. We note how limitations due to data sources can be mitigated and consider several ethical decisions in setting equitable enrollment goals.

Identifiants

pubmed: 37054773
pii: S1551-7144(23)00107-6
doi: 10.1016/j.cct.2023.107184
pii:
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

107184

Informations de copyright

Copyright © 2023 Pfizer. Published by Elsevier Inc. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interest The author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: LJR, PFT, SA, ARL, SS, MMR, CSP, LM are current employees of Pfizer Inc. Other authors declare that there is no direct conflict of interest related to this study.

Auteurs

Mark R Cullen (MR)

Department of Medicine, Biomedical Data Science and Health Policy, Stanford University, Stanford, CA, USA.

Adina R Lemeshow (AR)

Pfizer Inc., NY, USA.

Sandra Amaro (S)

Pfizer Inc., NY, USA.

Elisa V Bandera (EV)

Cancer Epidemiology and Health Outcomes, Rutgers Cancer Institute of New Jersey, New Brunswick, NJ, USA.

Lisa A Cooper (LA)

Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.

Ichiro Kawachi (I)

Department of Social Epidemiology, Harvard University, Cambridge, MA, USA.

Joseph Lunyera (J)

Division of General Internal Medicine, Department of Medicine, Duke University, Durham, NC, USA.

Laura McKinley (L)

Pfizer Inc., NY, USA.

Christopher S Poss (CS)

Pfizer Inc., NY, USA.

Melinda M Rottas (MM)

Pfizer Inc., NY, USA.

Stephen E Schachterle (SE)

Pfizer Inc., NY, USA.

Peter F Thadeio (PF)

Pfizer Inc., NY, USA.

Leo J Russo (LJ)

Pfizer Inc., NY, USA. Electronic address: leo.j.russo@pfizer.com.

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Classifications MeSH