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

S. Donegan, P. Williamson, Umberto D'Alessandro, P. Garner, C.T. Smith

    Research output: Contribution to journalA1: Web of Science-article

    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.
    Original languageEnglish
    JournalStatistics in Medicine
    Volume32
    Issue number6
    Pages (from-to)914-930
    Number of pages17
    ISSN0277-6715
    DOIs
    Publication statusPublished - 2013

    Keywords

    • Protozoal diseases
    • Malaria
    • Plasmodium falciparum
    • Vectors
    • Mosquitoes
    • Anopheles
    • Patient records
    • Data analysis
    • Methodology
    • Clinical trials
    • Statistical analysis
    • Statistical modeling
    • Treatment outcomes
    • Meta-analysis

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