通过使用不同链接的数据集,对多病症的可靠测量
Regina Prigge1, Kelly J Fleetwood2, Caroline A Jackson2
1Usher Institute, University of Edinburgh, Edinburgh, UK. regina.prigge@ed.ac.uk.
Communications medicine
|July 8, 2025
概括
关于多病症的研究,即多种长期疾病 (LTC) 的存在,是不一致的. 这项研究表明,数据源显著影响LTC和多病发病率的流行率估计,影响研究可重复性.
科学领域:
- 生物医学信息学 生物医学信息学
- 公共卫生研究 公共卫生研究
- 流行病学 流行病学
背景情况:
- 测量多病症 (多种长期疾病) 是不一致的,阻碍了研究的可重复性.
- 在一个人身上同时出现两个或两个以上的疾病被称为多病症.
研究的目的:
- 评估不同数据来源如何影响80种长期疾病 (LTC) 和多病症的估计患病率.
- 为了比较从初级保健记录,英国生物库基线评估和医院/癌症注册数据中得出的患病率估计.
主要方法:
- 使用了来自172,563名英国生物库参与者的数据的横截面方法.
- 开发了基于代码列表的算法,以确定在三个不同的数据源中LTC的流行率.
- 分析了使用初级保健记录,英国生物银行基线数据,医院/癌症登记记录以及所有三者的组合来分析患病率.
主要成果:
- 综合所有数据来源,85.1%的参与者至少有一个LTC,63.5%的参与者至少有两个LTC.
- 数据来源的选择对患病率估计有很大影响,在所有三种来源中,对于识别患有该病的人来说,一致性很低 (中位数为4.7%).
- 对于内分泌疾病,一致性最高,对于生殖尿路和精神/行为障碍,一致性最低,初级保健数据经常识别独特的病例.
结论:
- 数据来源的选择极大地影响了对个体LTC和多病症的研究结果.
- 研究人员必须清楚地证明他们选择的数据来源,以确保多病症研究的透明度和可重复性.
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