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Meta-analysis of a binary outcome using individual participant data and aggregate data.

Authors
  • Riley, Richard D
  • Steyerberg, Ewout W
Type
Published Article
Journal
Research synthesis methods
Publication Date
Jan 01, 2010
Volume
1
Issue
1
Pages
2–19
Identifiers
DOI: 10.1002/jrsm.4
PMID: 26056090
Source
Medline
Keywords
License
Unknown

Abstract

In this paper, we develop meta-analysis models that synthesize a binary outcome from health-care studies while accounting for participant-level covariates. In particular, we show how to synthesize the observed event-risk across studies while accounting for the within-study association between participant-level covariates and individual event probability. The models are adapted for situations where studies provide individual participant data (IPD), or a mixture of IPD and aggregate data. We show that the availability of IPD is crucial in at least some studies; this allows one to model potentially complex within-study associations and separate them from across-study associations, so as to account for potential ecological bias and study-level confounding. The models can produce pertinent population-level and individual-level results, such as the pooled event-risk and the covariate-specific event probability for an individual. Application is made to 14 studies of traumatic brain injury, where IPD are available for four studies and the six-month mortality risk is synthesized in relation to individual age. The results show that as individual age increases the probability of six-month mortality also increases; further, the models reveal clear evidence of ecological bias, with the mean age in each study additionally influencing an individual's mortality probability. Copyright © 2010 John Wiley & Sons, Ltd.

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