Evidence map›Paper›PMID 20439481›Full record

SynthesisInternational journal of epidemiology2010

Statistical methods for the time-to-event analysis of individual participant data from multiple epidemiological studies.

Simon Thompson, Stephen Kaptoge, Ian White, Angela Wood, Philip Perry, John Danesh, Emerging Risk Factors Collaboration

Abstract readMeta-Analysis
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in International journal of epidemiology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 69 papers, 32 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
69citing papers in PubMed, 32 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

69 citing papers in PubMed, 32 syntheses or guidelines pooled it.

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  4. Influence of donor sex and age on graft outcome in kidney transplantation.Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association · 2024
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  18. Obesity and mortality: are the risks declining? Evidence from multiple prospective studies in the United States.Obesity reviews : an official journal of the International Association for the Study of Obesity · 2014
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9 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Simon ThompsonMRC Biostatistics Unit, Institute of Public Health, Cambridge, UK. simon.thompson@mrc-bsu.cam.ac.uk
Stephen Kaptoge
Ian White
Angela Wood
Philip Perry
John Danesh
Emerging Risk Factors Collaboration

Funding

SOUTH CAROLINA CLINICAL & TRANSLATIONAL RESEARCH INSTITUTE (SCTR)UL1RR029882 · NCRR · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI BRADY, KATHLEEN T. · 2009 to 2011
$10.1M
British Heart Foundation RG/07/008/23674British Heart Foundation RG/08/013/25942British Heart Foundation RG/08/014/24067Medical Research Council G0100222Medical Research Council G0401527Medical Research Council G0700463Medical Research Council G0902037Medical Research Council G19/35Medical Research Council G8802774Medical Research Council MC_U105260558Medical Research Council MC_U105260792NCRR NIH HHS UL1 RR029882
6 · The paper itself

Abstract

backgroundMeta-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.

methodsThis 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.

resultsAnalyses 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.

conclusionIncreasing 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.

Indexed as

Data Interpretation, StatisticalEpidemiologic MethodsAge FactorsCoronary DiseaseFibrinogenHumansProportional Hazards ModelsRisk FactorsSex FactorsSmokingTime FactorsFibrinogen

Identifiers

PMID20439481
PMCPMC2972437

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.