采用现实世界的数据进行癌症研究的OMOPCDM的采用:当前状态和机遇
Liwei Wang1, Andrew Wen1, Sunyang Fu1
1McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, TX, USA.
medRxiv : the preprint server for health sciences
|September 4, 2024
概括
本综述探讨了观察医学结果伙伴关系 (OMOP) 共同数据模型 (CDM) 如何支持癌症研究. 它强调了利用OMOP CDM生态系统推进癌症研究的当前研究,挑战和机会.
科学领域:
- 医疗信息学 医疗信息学
- 癌症研究 癌症研究
- 观察数据分析 观察数据分析
背景情况:
- 观察医学结果伙伴关系 (OMOP) 共同数据模型 (CDM) 通过分布式网络分析促进了大规模的癌症研究.
- OHDSI社区维护OMOP CDM,支持越来越多的癌症研究研究.
研究的目的:
- 为癌症研究全面审查OMOPCDM的采用.
- 为促进癌症研究提供有关利用OMOPCDM生态系统的见解.
主要方法:
- 关于OMOP CDM和癌症研究的已发表文章的文献搜索 (2010年1月 - 2023年12月).
- 将研究分类为临床专注的数据分析和基础设施开发主题.
- 开发用于数据提取和分析的图表表格.
主要成果:
- 综述中包括了50篇独特的文章.
- 30篇文章集中在数据分析,23篇关于基础设施发展,其中3篇重叠.
- 该审查映射了OMOPCDM癌症研究领域内现有研究的范围和主题.
结论:
- 在数据质量,高级分析,NLP用于表型数据和多站点评估方面确定了挑战和机会.
- 突出了研究工作的现状,以加强癌症研究的OMOPCDM生态系统.
- 为未来的研究方向提供了基础,以利用OMOP CDM用于癌症研究.
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