Cargando…

Assumptions of Mixed Treatment Comparisons in Health Technology Assessments - Challenges and Possible Steps for Practical Application

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 assumpti...

Descripción completa

Detalles Bibliográficos
Autores principales: Reken, Stefanie, Sturtz, Sibylle, Kiefer, Corinna, Böhler, Yvonne-Beatrice, Wieseler, Beate
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4979893/
https://www.ncbi.nlm.nih.gov/pubmed/27508415
http://dx.doi.org/10.1371/journal.pone.0160712
_version_ 1782447399395917824
author Reken, Stefanie
Sturtz, Sibylle
Kiefer, Corinna
Böhler, Yvonne-Beatrice
Wieseler, Beate
author_facet Reken, Stefanie
Sturtz, Sibylle
Kiefer, Corinna
Böhler, Yvonne-Beatrice
Wieseler, Beate
author_sort Reken, Stefanie
collection PubMed
description 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.
format Online
Article
Text
id pubmed-4979893
institution National Center for Biotechnology Information
language English
publishDate 2016
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-49798932016-08-25 Assumptions of Mixed Treatment Comparisons in Health Technology Assessments - Challenges and Possible Steps for Practical Application Reken, Stefanie Sturtz, Sibylle Kiefer, Corinna Böhler, Yvonne-Beatrice Wieseler, Beate PLoS One Research Article 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. Public Library of Science 2016-08-10 /pmc/articles/PMC4979893/ /pubmed/27508415 http://dx.doi.org/10.1371/journal.pone.0160712 Text en © 2016 Reken et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Reken, Stefanie
Sturtz, Sibylle
Kiefer, Corinna
Böhler, Yvonne-Beatrice
Wieseler, Beate
Assumptions of Mixed Treatment Comparisons in Health Technology Assessments - Challenges and Possible Steps for Practical Application
title Assumptions of Mixed Treatment Comparisons in Health Technology Assessments - Challenges and Possible Steps for Practical Application
title_full Assumptions of Mixed Treatment Comparisons in Health Technology Assessments - Challenges and Possible Steps for Practical Application
title_fullStr Assumptions of Mixed Treatment Comparisons in Health Technology Assessments - Challenges and Possible Steps for Practical Application
title_full_unstemmed Assumptions of Mixed Treatment Comparisons in Health Technology Assessments - Challenges and Possible Steps for Practical Application
title_short Assumptions of Mixed Treatment Comparisons in Health Technology Assessments - Challenges and Possible Steps for Practical Application
title_sort assumptions of mixed treatment comparisons in health technology assessments - challenges and possible steps for practical application
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4979893/
https://www.ncbi.nlm.nih.gov/pubmed/27508415
http://dx.doi.org/10.1371/journal.pone.0160712
work_keys_str_mv AT rekenstefanie assumptionsofmixedtreatmentcomparisonsinhealthtechnologyassessmentschallengesandpossiblestepsforpracticalapplication
AT sturtzsibylle assumptionsofmixedtreatmentcomparisonsinhealthtechnologyassessmentschallengesandpossiblestepsforpracticalapplication
AT kiefercorinna assumptionsofmixedtreatmentcomparisonsinhealthtechnologyassessmentschallengesandpossiblestepsforpracticalapplication
AT bohleryvonnebeatrice assumptionsofmixedtreatmentcomparisonsinhealthtechnologyassessmentschallengesandpossiblestepsforpracticalapplication
AT wieselerbeate assumptionsofmixedtreatmentcomparisonsinhealthtechnologyassessmentschallengesandpossiblestepsforpracticalapplication