改善临床试验种族/种族报告和更新的包容性概况,2017-2022:新泽西州的快照
Elli Gourna Paleoudis1,2, Zhiyong Han1, Simon Gelman2
1Department of Medical Sciences, Hackensack Meridian School of Medicine, Nutley, NJ, USA.
Global epidemiology
|January 23, 2024
概括
新泽西州的临床试验显示,种族/种族报告和黑人参与者纳入情况有所改善,尽管亚裔和西班牙裔的代表性落后于人口普查数据. 目前正在努力提高试验公平性和通用性.
科学领域:
- 临床研究方法论临床研究方法论
- 卫生公平性健康公平性
- 生物统计学 生物统计学
背景情况:
- 临床试验中的多样化代表性对于医学干预测试至关重要,但已经不均地实现.
- 提高试验公平性和包容性是各种利益相关者不断努力的努力.
- 这项研究考察了新泽西州的临床试验报告和人口包容性.
研究的目的:
- 在新泽西州进行的临床试验中分析性别,种族和族裔报告.
- 将新泽西州临床试验中的参与者人口统计数据与美国人口普查数据进行比较.
- 在五年内评估临床试验包容性和报告的趋势.
主要方法:
- 利用clinicaltrials.gov注册表识别了2017年1月至2022年10月期间启动的481项临床试验.
- 分析了这些试验的性别/种族/种族报告和招生数据.
- 对229项美国试验进行了元分析,以将参与者比例与2020年美国人口普查数据进行比较.
主要成果:
- 超过97%的试验报告了种族/种族;所有报告的性别,不受资金或治疗领域的影响.
- 在美国的试验中,参与者中有76.7%是白人,14.1%是黑人,2.7%是亚裔,15%是西班牙裔.
- 黑人参与者的纳入与人口普查数据相匹配,而亚裔和西班牙裔参与率低于人口普查百分比.
结论:
- 新泽西州的临床试验报告和包容性在过去五年中呈现出上升趋势.
- 虽然取得了进展,但需要进一步努力,以使人口代表性与人口普查数据保持一致.
- 提高包容性和透明报告对于建立公众信任和确保试验结果的普遍性至关重要.
相关概念视频
Clinical Trials
6.7K
Clinical trials are prospective experimental studies conducted on humans to determine the safety and efficacy of treatments, drugs, diet methods, and medical devices. Using statistics in clinical trials enables researchers to derive reasonable and accurate conclusions from the collected data, allowing them to make wise decisions in uncertain situations. In medical research, statistical methods are crucial for preventing errors and bias.
There are four phases in a clinical trial. A phase one...
There are four phases in a clinical trial. A phase one...
6.7K
Bias in Epidemiological Studies
274
Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:
274
Prevalence and Incidence
534
In statistical epidemiology and health sciences, two essential metrics—prevalence and incidence—are fundamental for understanding disease dynamics within a population. These measures enable public health officials, epidemiologists, and researchers to assess the burden of diseases, allocate resources effectively, and design impactful public health policies and interventions.
Prevalence indicates the proportion of individuals in a population who have a specific disease or health...
Prevalence indicates the proportion of individuals in a population who have a specific disease or health...
534
Longitudinal Studies
165
Longitudinal studies are also widely used in other medical and social science fields. For instance, in cardiovascular research, they can monitor patients' health over decades to identify risk factors for heart disease, such as high cholesterol or smoking, and evaluate the long-term effectiveness of preventive measures. Similarly, in mental health studies, researchers might follow individuals from adolescence into adulthood to understand the development and progression of conditions like...
165
Statistical Software for Data Analysis and Clinical Trials
558
Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
558
Study Designs in Epidemiology
220
Epidemiological study designs are fundamental tools for investigating the distribution, determinants, and control of health conditions in populations. They help researchers understand the relationships between exposures and outcomes, and they broadly fall into two categories: "observational" and "experimental" studies.
Observational studies are those where the researcher does not intervene but rather observes natural variations. They include cross-sectional, cohort, and...
Observational studies are those where the researcher does not intervene but rather observes natural variations. They include cross-sectional, cohort, and...
220


