基于国家健康数据的多种癌症风险分层:一项追溯建模和验证研究
Alexander W Jung1, Peter C Holm2, Kumar Gaurav3
1European Molecular Biology Laboratory, European Bioinformatics Institute EMBL-EBI, Hinxton, UK; University of Cambridge, Cambridge, UK.
The Lancet. Digital health
|May 24, 2024
概括
电子健康记录可以预测跨人群的癌症风险. 在丹麦开发的泛癌风险模型表现良好,并将其推广到英国生物银行,帮助风险分层和潜在查工作.
科学领域:
- 计算流行病学计算流行病学
- 医疗信息学 医疗信息学
- 在瘤学瘤学.
背景情况:
- 医疗保健数字化正在增加,国家健康数据资源正在实施.
- 现有的癌症风险模型尚未完全探索不同癌症类型的人口水平风险分层.
- 本研究通过使用电子健康记录评估泛癌风险模型来弥补这一差距.
研究的目的:
- 评估基于电子健康记录 (EHR) 的泛癌风险模型.
- 评估这些模型在不同类型癌症中对人口水平风险分层的有用性.
- 在外部队列 (英国生物库) 中验证模型.
主要方法:
- 使用丹麦健康登记册和英国生物银行数据进行的回顾性建模和验证研究.
- 开发依赖时间的贝叶斯式Cox危险模型,使用来自病史,文本挖掘因素和家族史的1392个共变量.
- 丹麦数据的内部验证 (1995-2018) 和英国生物库数据的外部验证 (50-75岁).
- 主要结果:区分和校准性能.
主要成果:
- 丹麦数据包括超过670万个人;英国生物银行包括超过377,000人.
- 模型在丹麦显示出良好的歧视 (一致性指数0.81),根据癌症类型的变化 (0.66-0.91).
- 英国生物库的外部验证显示了类似的性能 (一致性指数0.66),表明了可概括性.
- 对消化系统,甲状腺,脏和子宫癌观察到的最佳性能.
结论:
- 电子健康记录数据可用于估计癌症风险因素,并使大多数癌症类型的风险预测成为可能.
- 开发的风险模型证明了丹麦和英国医疗保健系统之间的通用性.
- 基于EHR的风险模型可能会补充查工作,特别是随着多种癌症早期检测测试的出现.
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