Journal article
Statistical methods for the time-to-event analysis of individual participant data from multiple epidemiological studies
International journal of epidemiology, Vol.39(5), pp.1345-1359
10/01/2010
DOI: 10.1093/ije/dyq063
PMCID: PMC2972437
PMID: 20439481
Abstract
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.
Details
- Title: Subtitle
- Statistical methods for the time-to-event analysis of individual participant data from multiple epidemiological studies
- Creators
- Simon Thompson - MRC Biostatistics UnitStephen Kaptoge - MRC Biostatistics UnitIan White - MRC Biostatistics UnitAngela Wood - MRC Biostatistics UnitPhilip Perry - MRC Biostatistics UnitJohn Danesh - MRC Biostatistics UnitEmerging Risk Factors Collaboration
- Contributors
- R Wallace (Contributor) - University of Iowa, Internal Medicine
- Resource Type
- Journal article
- Publication Details
- International journal of epidemiology, Vol.39(5), pp.1345-1359
- DOI
- 10.1093/ije/dyq063
- PMID
- 20439481
- PMCID
- PMC2972437
- NLM abbreviation
- Int J Epidemiol
- ISSN
- 0300-5771
- eISSN
- 1464-3685
- Publisher
- Oxford Univ Press
- Number of pages
- 15
- Grant note
- UL1RR029882 / NATIONAL CENTER FOR RESEARCH RESOURCES; United States Department of Health & Human Services; National Institutes of Health (NIH) - USA; NIH National Center for Research Resources (NCRR) UK Medical Research Council; UK Research & Innovation (UKRI); Medical Research Council UK (MRC) G0700463 / MRC; UK Research & Innovation (UKRI); Medical Research Council UK (MRC) British Heart Foundation GlaxoSmithKline RG/08/013/25942 / British Heart Foundation ES/G007438/1 / ESRC; UK Research & Innovation (UKRI); Economic & Social Research Council (ESRC) ES/G007438/1 / Economic and Social Research Council; UK Research & Innovation (UKRI); Economic & Social Research Council (ESRC) MC_U105260558 / Medical Research Council; UK Research & Innovation (UKRI); Medical Research Council UK (MRC); European Commission BUPA Foundation
- Language
- English
- Date published
- 10/01/2010
- Academic Unit
- Epidemiology; Injury Prevention Research Center; Internal Medicine
- Record Identifier
- 9984363630602771
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