基于共同数据模型的药物流行病学研究:系统审查和文献分析分析.
Yongqi Zheng1, Meng Zhang1, Conghui Wang1
1Department of Epidemiology and Biostatistics, School of Public Health, Peking University, 38 Xueyuan Road, Haidian District, Beijing, 100191, China, 86 13811155891.
JMIR medical informatics
|July 28, 2025
概括
药物流行病学中的共同数据模型 (CDM) 允许进行大规模研究. 高影响力的研究往往涉及多中心合作和疫苗研究,强调全球包容性的需要.
科学领域:
- 药理流行病学 药理流行病学
- 现实世界的证据.
- 数据标准化数据标准化
背景情况:
- 共同数据模型 (CDM) 标准化了药物流行病学研究的数据.
- CDM促进了大规模的多中心研究和现实世界的证据生成.
- 在此领域缺乏CDM应用的全面全球评估.
研究的目的:
- 系统地审查和图书统计分析CDM在药理流行病学中的使用情况.
- 绘制CDM研究的出版趋势,机构合作和引用影响的地图.
- 确定与此领域的高影响力研究相关的因素.
主要方法:
- 从9个数据库中对308项研究 (1997-2024) 进行了系统审查和文献计量分析.
- 研究被按每年引用总量 (TCpY) 分类,以分析影响.
- 高TCpY与低TCpY研究的比较分析.
主要成果:
- 美国和韩国是基于CDM的药物流行病学领域的领先贡献者.
- 高TCpY研究与多中心合作,美国机构和疫苗研究有显著的关联.
- 国际合作集中在北美,欧洲和东亚,LMIC参与有限.
结论:
- 这项研究提供了第一个基于CDM的药物流行病学研究的文献统计概述.
- 多中心,协作和以疫苗为中心的研究表明影响力更高.
- 增加全球包容性和合作对于推动药物流行病学至关重要.
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