个体参与者数据的荟萃分析与连续暴露：案例研究。
Meta-analysis for individual participant data with a continuous exposure: A case study.
机构信息
University of Queensland, School of Public Health, Faculty of Medicine, Queensland, Australia.
School of Medicine, University of Leeds, Leeds, UK.
出版信息
J Clin Epidemiol. 2021 Dec;140:79-92. doi: 10.1016/j.jclinepi.2021.08.033. Epub 2021 Sep 4.
OBJECTIVE
Methods for meta-analysis of studies with individual participant data and continuous exposure variables are well described in the statistical literature but are not widely used in clinical and epidemiological research. The purpose of this case study is to make the methods more accessible.
STUDY DESIGN AND SETTING
A two-stage process is demonstrated. Response curves are estimated separately for each study using fractional polynomials. The study-specific curves are then averaged pointwise over all studies at each value of the exposure. The averaging can be implemented using fixed effects or random effects methods.
RESULTS
The methodology is illustrated using samples of real data with continuous outcome and exposure data and several covariates. The sample data set, segments of Stata and R code, and outputs are provided to enable replication of the results.
CONCLUSION
These methods and tools can be adapted to other situations, including for time-to-event or categorical outcomes, different ways of modelling exposure-outcome curves, and different strategies for covariate adjustment.
目的
个体参与者数据和连续暴露变量的荟萃分析方法在统计学文献中有很好的描述，但在临床和流行病学研究中并未得到广泛应用。本案例研究旨在使这些方法更易于使用。
研究设计和设置
演示了一个两阶段过程。使用分数多项式分别为每个研究估计响应曲线。然后，在每个暴露值处，通过固定效应或随机效应方法在所有研究中对研究特异性曲线进行逐点平均。
结果
使用具有连续结果和暴露数据以及多个协变量的真实数据样本说明了该方法。提供了样本数据集、Stata 和 R 代码片段以及输出，以能够复制结果。
结论
这些方法和工具可以适应其他情况，包括用于事件时间或分类结果、不同的暴露-结果曲线建模方式以及不同的协变量调整策略。
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