Statistical methods for the time-to-event analysis of individual participant data from multiple epidemiological studies.
Statistical methods for the time-to-event analysis of individual participant data from multiple epidemiological studies.
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DOI：
10.1093/ije/dyq063
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发表时间：
2010-10
影响因子：
7.7
通讯作者：
Emerging Risk Factors Collaboration
中科院分区：
文献类型：
--
作者：
Thompson S;Kaptoge S;White I;Wood A;Perry P;Danesh J;Emerging Risk Factors Collaboration
背景来自多项前瞻性流行病学研究的个体参与者发病时间数据的荟萃分析能够对暴露-风险关系进行详细的调查，但涉及到许多分析挑战。方法本文描述了新兴风险因素协作中采用的统计方法，其中对100多项前瞻性研究中100多万参与者的原始数据进行了整理，以便能够详细分析与心血管疾病事件结果相关的各种风险标记物。结果分析主要基于按性别分层的COX比例风险回归模型，分别在每项研究中进行。暴露-风险关系的估计最初未经调整，然后针对几个混杂因素进行了调整，在使用荟萃分析的研究中进行了合并。已经制定了评估暴露-风险关联形式和比例风险假设的方法。交互作用的估计也使用荟萃分析结合起来，将研究内部和研究之间的信息分开保存。通过对重复测量的分析以估计校正的回归系数，解决了由测量误差以及暴露和混杂因素中的人内差异引起的回归稀释偏差。这些方法以血浆纤维蛋白原和冠心病风险分析为例，并提供了STATA代码。结论对来自观察性数据的个体参与者数据进行了越来越多的荟萃分析，以增强流行病学研究的统计能力和细节。这里开发的统计方法可以用来满足这种分析的需要。
Background Meta-analysis of individual participant time-to-event data from multiple prospective epidemiological studies enables detailed investigation of exposure–risk relationships, but involves a number of analytical challenges. Methods This article describes statistical approaches adopted in the Emerging Risk Factors Collaboration, in which primary data from more than 1 million participants in more than 100 prospective studies have been collated to enable detailed analyses of various risk markers in relation to incident cardiovascular disease outcomes. Results Analyses have been principally based on Cox proportional hazards regression models stratified by sex, undertaken in each study separately. Estimates of exposure–risk relationships, initially unadjusted and then adjusted for several confounders, have been combined over studies using meta-analysis. Methods for assessing the shape of exposure–risk associations and the proportional hazards assumption have been developed. Estimates of interactions have also been combined using meta-analysis, keeping separate within- and between-study information. Regression dilution bias caused by measurement error and within-person variation in exposures and confounders has been addressed through the analysis of repeat measurements to estimate corrected regression coefficients. These methods are exemplified by analysis of plasma fibrinogen and risk of coronary heart disease, and Stata code is made available. Conclusion Increasing numbers of meta-analyses of individual participant data from observational data are being conducted to enhance the statistical power and detail of epidemiological studies. The statistical methods developed here can be used to address the needs of such analyses.
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影响因子：
120.7
作者：
Erqou, Sebhat;Kaptoge, Stephen;Perry, Philip L.;Di Angelantonio, Emanuele;Thompson, Alexander;White, Ian R.;Marcovina, Santica M.;Collins, Rory;Thompson, Simon G.;Danesh, John
通讯作者：
Danesh, John
影响因子：
2
作者：
Govindarajulu, Usha S.;Spiegelman, Donna;Eisen, Ellen A.
通讯作者：
Eisen, Ellen A.
影响因子：
2.2
作者：
DerSimonian, Rebecca;Kacker, Raghu
通讯作者：
Kacker, Raghu
影响因子：
37.8
作者：
Cook, Nancy R.
通讯作者：
Cook, Nancy R.
DOI：
10.1016/0197-2456(86)90046-2
发表时间：
1986-09-01
期刊：
CONTROLLED CLINICAL TRIALS
影响因子：
--
作者：
DERSIMONIAN, R;LAIRD, N
通讯作者：
LAIRD, N