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Combining individual patient data and aggregate data in mixed treatment comparison meta-analysis: Individual patient data may be beneficial if only for a subset of trials

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dc.contributor.author Donegan, S.
dc.contributor.author Williamson, P.
dc.contributor.author D'Alessandro, U.
dc.contributor.author Garner, P.
dc.contributor.author Smith, C. T.
dc.date.accessioned 2013-05-24T09:47:33Z
dc.date.available 2013-05-24T09:47:33Z
dc.date.issued 2013
dc.identifier.issn 0277-6715
dc.identifier.doi http://dx.doi.org/10.1002/sim.5584
dc.identifier.other ITG-B3A
dc.identifier.other DBM
dc.identifier.other U-MALAR
dc.identifier.other DOI
dc.identifier.other JIF
dc.identifier.other Abstract
dc.identifier.other UPD55
dc.identifier.uri http://hdl.handle.net/10390/7437
dc.description.abstract Background Individual patient data (IPD) meta-analysis is the gold standard. Aggregate data (AD) and IPD can be combined using conventional pairwise meta-analysis when IPD cannot be obtained for all relevant studies. We extend the methodology to combine IPD and AD in a mixed treatment comparison (MTC) meta-analysis. Methods The proposed random-effects MTC models combine IPD and AD for a dichotomous outcome. We study the benefits of acquiring IPD for a subset of trials when assessing the underlying consistency assumption by including treatment-by-covariate interactions in the model. We describe three different model specifications that make increasingly stronger assumptions regarding the interactions. We illustrate the methodology through application to real data sets to compare drugs for treating malaria by using the outcome unadjusted treatment success at day 28. We compare results from AD alone, IPD alone and all data. Results When IPD contributed (i.e. either using IPD alone or combining IPD and AD), the chains converged, and we identified statistically significant regression coefficients for the interactions. Using IPD alone, we were able to compare only three of the six treatments of interest. When models were fitted to AD, the treatment effects and regression coefficients for the interactions were far more imprecise, and the chains did not converge. Conclusions The models combining IPD and AD encapsulated all available evidence. When exploring interactions, it can be beneficial to obtain IPD for a subset of trials and to combine IPD with additional AD. Copyright (c) 2012 John Wiley & Sons, Ltd. en
dc.language English en
dc.subject Protozoal diseases en
dc.subject Malaria en
dc.subject Plasmodium falciparum en
dc.subject Vectors en
dc.subject Mosquitoes en
dc.subject Anopheles en
dc.subject Patient records en
dc.subject Data analysis en
dc.subject Methodology en
dc.subject Clinical trials en
dc.subject Statistical analysis en
dc.subject Statistical modeling en
dc.subject Treatment outcomes en
dc.subject Meta-analysis en
dc.title Combining individual patient data and aggregate data in mixed treatment comparison meta-analysis: Individual patient data may be beneficial if only for a subset of trials en
dc.type Article en
dc.citation.issue 6 en
dc.citation.jtitle Statistics in Medicine en
dc.citation.volume 32 en
dc.citation.pages 914-930 en
dc.identifier.pmid http://www.ncbi.nlm.nih.gov/pubmed/22987606
dc.citation.jabbreviation Stat Med en


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