Dataset Information

A model for meta-analysis of correlated binary outcomes: The case of split-body interventions.

ABSTRACT: In several areas of clinical research, it is common for trials to assign different sites of the participants' bodies to different interventions. For example, a randomized controlled trial comparing surgical techniques for correcting myopia may randomize each eye of a participant to a different operation. Under such bilateral ('split-body') interventions, the observations from each participant are correlated. It is challenging to account for these correlations at the meta-analysis level, especially when the outcome is rare. Here, we present a meta-analysis model based on the bivariate binomial distribution. Our model can synthesize studies on patients who received one intervention at one body site, patients who received two interventions at different sites or a mixture of these two groups. The model can analyse studies with zero events in one or both treatment arms and can handle the case of incomplete data reporting. We use simulations to assess the performance of our model and to compare it with the bivariate beta-binomial model. In the case of bilateral interventions, our model performed well and outperformed the bivariate beta-binomial model in all scenarios explored. We illustrate our methods using two previously published meta-analyses from the fields of orthopaedics and ophthalmology. We conclude that our model constitutes a useful new tool for the meta-analysis of binary outcomes in the presence of split-body interventions.

SUBMITTER: Efthimiou O

PROVIDER: S-EPMC6613182 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A model for meta-analysis of correlated binary outcomes: The case of split-body interventions.

Efthimiou Orestis O Mavridis Dimitris D Nikolakopoulou Adriani A Rücker Gerta G Trelle Sven S Egger Matthias M Salanti Georgia G

Statistical methods in medical research 20171212 7

In several areas of clinical research, it is common for trials to assign different sites of the participants' bodies to different interventions. For example, a randomized controlled trial comparing surgical techniques for correcting myopia may randomize each eye of a participant to a different operation. Under such bilateral ('split-body') interventions, the observations from each participant are correlated. It is challenging to account for these correlations at the meta-analysis level, especial ...[more]

PMID: 29233084

Similar Datasets

Project description:BackgroundMeta-analyses (MA) based on individual patient data (IPD) are regarded as the gold standard for meta-analyses and are becoming increasingly common, having several advantages over meta-analyses of summary statistics. These analyses are being undertaken in an increasing diversity of settings, often having a binary outcome. In a previous systematic review of articles published between 1999-2001, the statistical approach was seldom reported in sufficient detail, and the outcome was binary in 32% of the studies considered. Here, we explore statistical methods used for IPD-MA of binary outcomes only, a decade later.MethodsWe selected 56 articles, published in 2011 that presented results from an individual patient data meta-analysis. Of these, 26 considered a binary outcome. Here, we review 26 IPD-MA published during 2011 to consider: the goal of the study and reason for conducting an IPD-MA, whether they obtained all the data they sought, the approach used in their analysis, for instance, a two-stage or a one stage model, and the assumption of fixed or random effects. We also investigated how heterogeneity across studies was described and how studies investigated the effects of covariates.Results19 of the 26 IPD-MA used a one-stage approach. 9 IPD-MA used a one-stage random treatment-effect logistic regression model, allowing the treatment effect to vary across studies. Twelve IPD-MA presented some form of statistic to measure heterogeneity across studies, though these were usually calculated using two-stage approach. Subgroup analyses were undertaken in all IPD-MA that aimed to estimate a treatment effect or safety of a treatment,. Sixteen meta-analyses obtained 90% or more of the patients sought.ConclusionEvidence from this systematic review shows that the use of binary outcomes in assessing the effects of health care problems has increased, with random effects logistic regression the most common method of analysis. Methods are still often not reported in enough detail. Results also show that heterogeneity of treatment effects is discussed in most applications.

Dataset Information

A model for meta-analysis of correlated binary outcomes: The case of split-body interventions.

Publications

A model for meta-analysis of correlated binary outcomes: The case of split-body interventions.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets