The use of single armed observational data to closing the gap in otherwise disconnected evidence networks: a network meta-analysis in multiple myeloma
Schmitz, Susanne Maguire, Áine Morris, James Ruggeri, Kai Haller, Elisa Kuhn, Isla Leahy, Joy Homer, Natalia Khan, Ayesha Bowden, Jack
Schmitz, Susanne
Maguire, Áine
Morris, James
Ruggeri, Kai
Haller, Elisa
Kuhn, Isla
Leahy, Joy
Homer, Natalia
Khan, Ayesha
Bowden, Jack
Identifiers
http://hdl.handle.net/10379/13830
https://doi.org/10.13025/27324
https://doi.org/10.13025/27324
Repository DOI
Publication Date
2018-06-28
Keywords
network meta-analysis, single armed studies, evidence synthesis, relapsed or refractory myeloma, lenalidomide plus dexamethasone, adjusted indirect comparisons, mixed treatment comparisons, low-dose dexamethasone, randomized phase-iii, propensity score, refractory myeloma, treatment outcomes, bortezomib, therapy
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Article
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Citation
Schmitz, Susanne; Maguire, Áine; Morris, James; Ruggeri, Kai; Haller, Elisa; Kuhn, Isla; Leahy, Joy; Homer, Natalia; Khan, Ayesha; Bowden, Jack; Buchanan, Vanessa; O’Dwyer, Michael; Cook, Gordon; Walsh, Cathal (2018). The use of single armed observational data to closing the gap in otherwise disconnected evidence networks: a network meta-analysis in multiple myeloma. BMC Medical Research Methodology 18 ,
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.
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Publisher
Springer Nature
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Attribution-NonCommercial-NoDerivs 3.0 Ireland