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Assessing the impact of a matching adjusted indirect comparison in a bayesian network meta analysis

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dc.contributor.author Leahy, Joy
dc.contributor.author Walsh, Cathal Dominic
dc.date.accessioned 2020-01-27T12:27:28Z
dc.date.issued 2019
dc.identifier.uri http://hdl.handle.net/10344/8428
dc.description peer-reviewed en_US
dc.description.abstract if IPD is available for some or all trials in an NMA, then incorporating this IPD into an NMA is routinely considered to be preferable. However, the situation often arises where a researcher has IPD for trials concerning a particular treatment (for example from a spon- sor), but none for other trials. Therefore, one can reweight the IPD so that the covariate characteristics in the IPD trials match that of the aggregate data (AgD) trials, using a Matching Adjusted Indirect Comparison (MAIC). We assess the impact of using the reweighted aggregated data, obtained by the MAIC, in a Bayesian NMA for a connected treatment network. We apply this method to a network of multiple myeloma treatments in newly diagnosed patients (ndMM), where the outcome is progression free survival. We investigate the reliability of the methods and results through a simulation study. The ndMM network con-sists of three IPD studies comparing lenalidomide to placebo (Len-Placebo), one AgD study comparing Len-Placebo, and one AgD study comparing thalidomide to placebo (Thal-Placebo). We therefore investigate two options of weighting the covariates: 1. all three studies are weighted separately to match the AgD Thal-Placebo trial. 2. patients are weighted across all three IPD studies to match the AgD Thal-Placebo trial, but the NMA considers each trial separately. We observe limited bene t to MAIC in the full network population. While MAIC can be beneficial as a sensitivity analysis to confirm results across patient populations, we advise that MAIC is used and interpreted with caution. en_US
dc.language.iso eng en_US
dc.publisher Wiley and Sons Ltd. en_US
dc.relation 08INI1879 en_US
dc.relation.ispartofseries Research Synthesis Methods;10(4), pp. 546–568
dc.relation.uri http://dx.doi.org/10.1002/jrsm.1372
dc.rights This is the peer reviewed version of the following article:Assessing the impact of a matching adjusted indirect comparison in a bayesian network meta analysisResearch Synthesis Methods Wiley 2019, 10,pp. 546–568 which has been published in final form at http://dx.doi.org/10.1002/jrsm.1372 This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving. en_US
dc.subject MAIC en_US
dc.subject IPD en_US
dc.subject free survival en_US
dc.title Assessing the impact of a matching adjusted indirect comparison in a bayesian network meta analysis en_US
dc.type info:eu-repo/semantics/article en_US
dc.type.supercollection all_ul_research en_US
dc.type.supercollection ul_published_reviewed en_US
dc.identifier.doi 10.1002/jrsm.1372
dc.contributor.sponsor HRB en_US
dc.contributor.sponsor SFI en_US
dc.relation.projectid RL2013/4 en_US
dc.relation.projectid 08/IN.1/I1879 en_US
dc.date.embargoEndDate 2020-08-01
dc.embargo.terms 2020-08-01 en_US
dc.rights.accessrights info:eu-repo/semantics/openAccess en_US
dc.internal.rssid 2933398


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