title: Assumptions of Mixed Treatment Comparisons in Health Technology Assessments - Challenges and Possible Steps for Practical Application.
abstract: The validity of mixed treatment comparisons (MTCs), also called network meta-analysis, relies on whether it is reasonable to accept the underlying assumptions on similarity, homogeneity, and consistency. The aim of this paper is to propose a practicable approach to addressing the underlying assumptions of MTCs. Using data from clinical studies of antidepressants included in a health technology assessment (HTA), we present a stepwise approach to dealing with challenges related to checking the above assumptions and to judging the robustness of the results of an MTC. At each step, studies that were dissimilar or contributed to substantial heterogeneity or inconsistency were excluded from the primary analysis. In a comparison of the MTC estimates from the consistent network with the MTC estimates from the homogeneous network including inconsistencies, few were affected by notable changes; that is, a change in effect size (factor 2), direction of effect or statistical significance. Considering the small proportion of studies excluded from the network due to inconsistency, as well as the number of notable changes, the MTC results were deemed sufficiently robust. In the absence of standard methods, our approach to checking assumptions in MTCs may inform other researchers in need of practical options, particularly in HTA.
authors: Department of Drug Assessment, Institute for Quality and Efficiency in Health Care, Cologne, Germany.
authors: Stefanie
authors: http://orcid.org/0000-0003-4239-504X
authors: S
authors: Reken
authors: Department of Medical Biometry, Institute for Quality and Efficiency in Health Care, Cologne, Germany.
authors: Sibylle
authors: S
authors: Sturtz
authors: Department of Medical Biometry, Institute for Quality and Efficiency in Health Care, Cologne, Germany.
authors: Corinna
authors: C
authors: Kiefer
authors: Department of Drug Assessment, Institute for Quality and Efficiency in Health Care, Cologne, Germany.
authors: Yvonne-Beatrice
authors: YB
authors: Böhler
authors: Department of Drug Assessment, Institute for Quality and Efficiency in Health Care, Cologne, Germany.
authors: Beate
authors: B
authors: Wieseler
mesh_terms: D000928:Antidepressive Agents / Q000191:economics / Q000627:therapeutic use*; D006801:Humans; D015233:Models, Statistical; D013673:Technology Assessment, Biomedical / Q000191:economics / Q000379:methods* / Q000592:standards; D016896:Treatment Outcome
chemical_list: D000928:Antidepressive Agents