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制定入组目标的框架,以确保美国资助的临床试验中参与者的多样性。

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

机构信息

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

Pfizer Inc., NY, USA.

出版信息

Contemp Clin Trials. 2023 Jun;129:107184. doi: 10.1016/j.cct.2023.107184. Epub 2023 Apr 11.

Abstract

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.

摘要

背景

临床试验(CTs)的多样性有可能改善公平性并缩小健康差距。历史上服务不足的群体代表性不足,会影响试验结果在目标人群中的普遍性,阻碍创新,并导致入组率低。本研究的目的是建立一个透明且可重复的过程,根据疾病流行病学设定具有包容性的试验入组目标。

方法

召集了一组具有健康差距、公平性、多样性和健康决定因素方面专业知识的流行病学家顾问委员会,以评估和加强初始目标设定框架。使用的数据源包括流行病学文献、美国人口普查和真实世界数据(RWD);适当考虑并解决了局限性。设计了一个框架来防止历史上医疗服务不足的群体代表性不足。创建了一个基于实证数据的是/否决策的逐步方法。

结果

我们比较了 Pfizer 产品组合中六种疾病的 RWD 中的种族和族裔分布,这些疾病代表了不同的治疗领域(多发性骨髓瘤、真菌感染、克罗恩病、戈谢病、COVID-19 和莱姆病)与美国人口普查中的分布,并确定了试验入组目标。多发性骨髓瘤、戈谢病和 COVID-19 的潜在 CT 入组目标基于 RWD;真菌感染、克罗恩病和莱姆病的入组目标基于人口普查。

结论

我们开发了一个透明且可重复的框架,用于设定 CT 多样性入组目标。我们注意到如何减轻由于数据源限制的影响,并在设定公平入组目标时考虑几个伦理决策。

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