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The use of single armed observational data to closing the gap in otherwise disconnected evidence networks: a network meta-analysis in multiple myeloma

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dc.contributor.author Schmitz, Susanne
dc.contributor.author Maguire, Áine
dc.contributor.author Morris, James
dc.contributor.author Ruggeri, Kai
dc.contributor.author Haller, Elisa
dc.contributor.author Kuhn, Isla
dc.contributor.author Leahy, Joy
dc.contributor.author Homer, Natalia
dc.contributor.author Khan, Ayesha
dc.contributor.author Bowden, Jack
dc.contributor.author Buchanan, Vanessa
dc.contributor.author O'Dwyer, Michael
dc.contributor.author Cook, Gordon
dc.contributor.author Walsh, Cathal Dominic
dc.date.accessioned 2018-07-27T08:23:43Z
dc.date.available 2018-07-27T08:23:43Z
dc.date.issued 2018
dc.identifier.uri http://hdl.handle.net/10344/6996
dc.description peer-reviewed en_US
dc.description.abstract Background: Network meta-analysis (NMA) allows for the estimation of comparative effectiveness of treatments that have not been studied in head-to-head trials; however, relative treatment effects for all interventions can only be derived where available evidence forms a connected network. Head-to-head evidence is limited in many disease areas, regularly resulting in disconnected evidence structures where a large number of treatments are available. This is also the case in the evidence of treatments for relapsed or refractory multiple myeloma. Methods: Randomised controlled trials (RCTs) identified in a systematic literature review form two disconnected evidence networks. Standard Bayesian NMA models are fitted to obtain estimates of relative effects within each network. Observational evidence was identified to fill the evidence gap. Single armed trials are matched to act as each other’s control group based on a distance metric derived from covariate information. Uncertainty resulting from including this evidence is incorporated by analysing the space of possible matches. Results: Twenty five randomised controlled trials form two disconnected evidence networks; 12 single armed observational studies are considered for bridging between the networks. Five matches are selected to bridge between the networks. While significant variation in the ranking is observed, daratumumab in combination with dexamethasone and either lenalidomide or bortezomib, as well as triple therapy of carfilzomib, ixazomib and elozumatab, in combination with lenalidomide and dexamethasone, show the highest effects on progression free survival, on average. Conclusions: The analysis shows how observational data can be used to fill gaps in the existing networks of RCT evidence; allowing for the indirect comparison of a large number of treatments, which could not be compared otherwise. Additional uncertainty is accounted for by scenario analyses reducing the risk of over confidence in interpretation of results. en_US
dc.language.iso eng en_US
dc.publisher BioMed Central en_US
dc.relation.ispartofseries BMC Medical Research Methodology;18:66
dc.relation.uri https://doi.org/10.1186/s12874-018-0509-7
dc.subject network meta-analysis en_US
dc.subject single armed studies en_US
dc.subject evidence synthesis en_US
dc.subject relapsed or refractory myeloma en_US
dc.title The use of single armed observational data to closing the gap in otherwise disconnected evidence networks: a network meta-analysis in multiple myeloma 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 10.1186/s12874-018-0509-7
dc.rights.accessrights info:eu-repo/semantics/openAccess en_US


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