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

Autor: Kai Ruggeri, Joy Leahy, Michael O'Dwyer, James Morris, Cathal Walsh, Natalia Homer, Áine Maguire, Gordon Cook, Susanne Schmitz, Jack Bowden, Vanessa Buchanan, Ayesha Khan, Elisa Haller, Isla Kuhn
Přispěvatelé: Schmitz, Susanne [0000-0003-4753-1709], Apollo - University of Cambridge Repository, Celgene
Jazyk: angličtina
Rok vydání: 2018
Předmět:
Epidemiology
Computer science
Network Meta-Analysis
treatment outcomes
randomized phase-iii
Dexamethasone
law.invention
Ixazomib
Bortezomib
chemistry.chemical_compound
0302 clinical medicine
Randomized controlled trial
law
Statistics
Antineoplastic Combined Chemotherapy Protocols
Network meta-analysis
Lenalidomide
Randomized Controlled Trials as Topic
Single armed studies
lcsh:R5-920
Medicine--Research--Data processing
lenalidomide plus dexamethasone
Antibodies
Monoclonal
Relapsed or refractory myeloma
Observational Studies as Topic
Systematic review
Evidence synthesis
030220 oncology & carcinogenesis
Meta-analysis
lcsh:Medicine (General)
Multiple Myeloma
Oligopeptides
Medicine--Research--Methodology
medicine.drug
Research Article
refractory myeloma
Bridging (networking)
Health Informatics
low-dose dexamethasone
03 medical and health sciences
Covariate
medicine
adjusted indirect comparisons
Humans
propensity score
therapy
Bayes Theorem
mixed treatment comparisons
Survival Analysis
chemistry
Observational study
030215 immunology
Systematic Reviews as Topic
Zdroj: Schmitz, S, Maguire, Á, Morris, J, Ruggeri, K, Haller, E, Kuhn, I, Leahy, J, Homer, N, Khan, A, Bowden, J, Buchanan, V, O'Dwyer, M, Cook, G & Walsh, C 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, vol. 18, no. 1, 66 . https://doi.org/10.1186/s12874-018-0509-7
BMC Medical Research Methodology
BMC Medical Research Methodology, Vol 18, Iss 1, Pp 1-18 (2018)
ISSN: 1471-2288
Popis: 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.
Databáze: OpenAIRE
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