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Lee: Meta-analysis
Review Article
Journal of Korean Endocrine Society

Journal of Korean Endocrine Society 2008; 23(6): 361-378.

Published online: 31 December 2008

DOI: https://doi.org/10.3803/jkes.2008.23.6.361

Meta-analysis

Juneyoung Lee

Department of Biostatistics, College of Medicine, Korea University, Seoul, Korea.

Copyright © 2008 Korean Endocrine Society

Figures and Tables

Fig. 1
A funnel plot of log odds ratios (ORs) of the incidence of myocardial infarction between rosiglitazone group and control group versus its standard error (SE). Data used was from the 42 trials displayed in Table 3 of Nissen and Wolski (2007).
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Fig. 2
A graphical representation of the concepts of (a) a fixed-effects model and (b) a random-effects model. A fixed-effects model assumes that there is a common 'true' treatment effect underlying studies and that each study result will vary randomly around this true effect (i.e., treatment effect for each study = common true treatment effect + study variation that called a random error). A random-effects model assumes that there is different underlying effect for each study and that there is also an additional source of variation between studies which reflects the amount of heterogeneity between them (i.e., treatment effect for each study = true average effect which follows a normal distribution + within study variation that called a random error).
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Fig. 3
A sample result of meta-analysis for the odds ratio (OR) of myocardial infarction (MI) between rosiglitazone group and control group using STATA software based on the data from the Table 3 of Nissen and Wolski (2007). Peto estimation method is used to combine the results of 38 trials. Four trials are excluded in the meta-analysis due to zero events observed in both groups.
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Fig. 4
A forest plot and the combined result of meta-analysis for the odds ratio (OR) of myocardial infarction (MI) between rosiglitazone group and control group. A fixed-effects model with Peto estimation method is used. Each of blocks represents the OR for each trial and the horizontal line indicates its 95% confidence interval (CI). The size of each block is approximately proportional to the statistical weight of the trial used in the meta-analysis. The diamond represents the pooled estimate and its 95% CI. The solid vertical line indicates no difference in the odds of MI between two groups, while the dashed vertical line represents the pooled effect. The left side of the solid vertical line represents lower odds of MI for rosiglitazone than for control, while the right side represents higher odds. Four trials are excluded in the meta-analysis due to zero events observed in both groups.
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Fig. 5
A plot for finding most influential trial in the result of meta-analysis for the odds ratio (OR) of myocardial infarction (MI) between rosiglitazone group and control group. Each of horizontal line indicates a repeated result of meta-analysis after omitting the corresponding trial in turn. Vertical solid lines represent Peto's pooled estimate and its 95% confidence interval using all of 38 trials.
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Table 1
Cochrane highly sensitive search strategy for identifying randomized trials in MEDLINE. Following examples are adapted from Higgins and Green (2008)
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Table 2
A fixed-effects model meta-analysis using inverse-variance weighted (IVW) estimation method to obtain a pooled odds ratio (OR) estimate and its 95% confidence interval (CI) based on 2 × 2 tables comparing binary outcome between treatment and control groups
jkes-23-361-i002
Table 3
A random-effects model meta-analysis using DerSimonian-Laired (DL) estimation method to obtain a pooled odds ratio (OR) estimate and its 95% confidence interval (CI) based on 2 × 2 tables comparing binary outcome between treatment and control groups
jkes-23-361-i003

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