公平的数据缺口和血红蛋白病研究中心之间的合作意愿
Stella Tamana1, Kristia Yiangou2, Kalia Orphanou1
1Department of Blood Disorder Genetics and Thalassemia, The Cyprus Institute of Neurology and Genetics, Nicosia, Cyprus.
Scientific data
|March 3, 2026
概括
血红蛋白病的研究需要更好的数据共享. 大多数中心缺乏FAIR数据原则,但愿意在乳血病和状细胞疾病的数据倡议上进行合作.
科学领域:
- 医疗信息学 医疗信息学
- 遗传学 遗传学 是一个
- 数据科学数据科学数据科学
背景情况:
- 像血病和状细胞病这样的血红蛋白病需要强大的数据系统来进行研究和护理.
- 当前的数据系统往往没有遵守可查找,可访问,可互操作和可重复使用 (FAIR) 原则.
- 有限的数据互操作性阻碍了多中心研究和协调治疗这些遗传性血液疾病.
研究的目的:
- 评估全球血红蛋白病症中心的数据管理实践和FAIR数据合规性.
- 评估采用元数据标准,本体学和常用数据模型的情况.
- 测量这些中心对数据共享和协作的准备程度.
主要方法:
- 在HELIOS网络中向数据专业人员,临床医生和研究人员分发了一项横截面的基于Web的调查.
- 分析了来自22个国家的44个机构的答案.
- 收集的数据集中在元数据文档,标准的使用,数据模型的实施,以及合作的意愿.
主要成果:
- 只有一半的中心报告了基本的元数据文档;20%使用了公认的实体学.
- 没有中心实施共同的数据模型 (例如,OMOP,CDISC),HL7 FHIR的采用有限.
- 核心数据集 (人口统计学,实验室,基因型) 是常见的,但omics和成像数据很少.
- 尽管FAIR遵守程度较低,但观察到对联合 (86%) 和集中 (68%) 数据共享的意愿很高.
结论:
- 在整个血红蛋白病研究中心的FAIR数据原则实施中存在显著的差距.
- 有相当大的协作潜力和意愿改善数据共享实践.
- 解决这些FAIR数据缺口对于推进多中心研究和改善血红蛋白病变患者护理至关重要.
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