邀请评论:不完整的死亡信息对累积风险估计的影响
1Department of Mathematics and Statistics, College of Arts and Sciences, Boston University, Boston, MA 02215,United States.
American journal of epidemiology
|July 25, 2024
概括
在死亡时进行审查可以在观察性研究中偏差估计,特别是在高死亡率的情况下. 这项研究提供了分析界限来评估偏见和指导,当死亡率数据对于准确的制药流行病学研究至关重要时.
科学领域:
- 药学流行病学 药学流行病学
- 生物统计学 生物统计学
- 观察性研究设计研究
背景情况:
- 在死亡时进行审查是观察性研究中常见的一种方法,当死亡数据无法获得时.
- 这种方法可能导致对事件概率的偏差估计,特别是当死亡率高时.
- 之前由Barberio等人进行的模拟. 证明了这种越来越多的偏差与更高的死亡率.
研究的目的:
- 通过在死亡时审查引入的偏见获得分析表达式.
- 为这种偏差提供上限,以告知死亡率数据的必要性.
- 提供何时获得死亡率信息的指导对于准确的药物流行病学至关重要.
主要方法:
- 导出一个分析公式来量化死后审查的偏差.
- 为偏差制定两个上限.
- 介绍了一种算法,用于在死亡的概率较低时构建更宽的置信区间 (CI).
主要成果:
- 由于在死亡时审查而导致的偏见的分析表达式得到了衍生.
- 建立了偏差的两个上限,以告知死亡率数据的价值.
- 结果表明,当偏差很大时,获得死亡率信息是必不可少的.
结论:
- 衍生出来的边界有助于评估死后审查对研究估计的影响.
- 在药理流行病学中,死亡率信息至关重要,以避免在观察性研究中出现重大偏差.
- 这些发现支持了纳入死亡率数据的实际重要性,正如Barberio等人所强调的那样.
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