Abstract
BackgroundMeta-analyses have become an essential tool in synthesizing evidence on clinical and epidemiological questions derived from a multitude of similar studies assessing the particular issue. Appropriate and accessible statistical software is needed to produce the summary statistic of interest.MethodsMetaprop is a statistical program implemented to perform meta-analyses of proportions in Stata. It builds further on the existing Stata procedure metan which is typically used to pool effects (risk ratios, odds ratios, differences of risks or means) but which is also used to pool proportions. Metaprop implements procedures which are specific to binomial data and allows computation of exact binomial and score test-based confidence intervals. It provides appropriate methods for dealing with proportions close to or at the margins where the normal approximation procedures often break down, by use of the binomial distribution to model the within-study variability or by allowing Freeman-Tukey double arcsine transformation to stabilize the variances. Metaprop was applied on two published meta-analyses: 1) prevalence of HPV-infection in women with a Pap smear showing ASC-US; 2) cure rate after treatment for cervical precancer using cold coagulation.ResultsThe first meta-analysis showed a pooled HPV-prevalence of 43% (95% CI: 38%-48%). In the second meta-analysis, the pooled percentage of cured women was 94% (95% CI: 86%-97%).ConclusionBy using metaprop, no studies with 0% or 100% proportions were excluded from the meta-analysis. Furthermore, study specific and pooled confidence intervals always were within admissible values, contrary to the original publication, where metan was used.Electronic supplementary materialThe online version of this article (doi:10.1186/2049-3258-72-39) contains supplementary material, which is available to authorized users.
Highlights
Meta-analyses have become an essential tool in synthesizing evidence on clinical and epidemiological questions derived from a multitude of similar studies assessing the particular issue
A new program in Stata to perform meta-analyses of binomial data to supplement the metan command, which is typically used to pool associations. metaprop builds further on the metan procedure
We present procedures specific to pooling of binomial data including methods of computation of the confidence intervals, continuity correct and the Freeman-Tukey transformation
Summary
Meta-analyses have become an essential tool in synthesizing evidence on clinical and epidemiological questions derived from a multitude of similar studies assessing the particular issue. Meta-analyses combine information from multiple studies in order to derive an average estimate. Different metaanalysis procedures exist depending on the statistic to be reported. Examples of statistics of interest include association measures such as risk difference, risk ratio, odds ratio, difference in means, or one-dimensional binomial or continuous measures such as proportions or means. There are three important aspects in meta-analysis: a) the analysis framework, b) the model and c) the choice of the method to estimate the heterogeneity parameter. A meta-analyst has a choice between the fixed- and random-effects model
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