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A threshold analysis assessed the credibility of conclusions from network meta-analysis

OBJECTIVE: To assess the reliability of treatment recommendations based on network meta-analysis (NMA). STUDY DESIGN AND SETTING: We consider evidence in an NMA to be potentially biased. Taking each pairwise contrast in turn, we use a structured series of threshold analyses to ask: (1) “How large wo...

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Autores principales: Caldwell, Deborah M., Ades, A.E., Dias, Sofia, Watkins, Sarah, Li, Tianjing, Taske, Nichole, Naidoo, Bhash, Welton, Nicky J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5176010/
https://www.ncbi.nlm.nih.gov/pubmed/27430731
http://dx.doi.org/10.1016/j.jclinepi.2016.07.003
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author Caldwell, Deborah M.
Ades, A.E.
Dias, Sofia
Watkins, Sarah
Li, Tianjing
Taske, Nichole
Naidoo, Bhash
Welton, Nicky J.
author_facet Caldwell, Deborah M.
Ades, A.E.
Dias, Sofia
Watkins, Sarah
Li, Tianjing
Taske, Nichole
Naidoo, Bhash
Welton, Nicky J.
author_sort Caldwell, Deborah M.
collection PubMed
description OBJECTIVE: To assess the reliability of treatment recommendations based on network meta-analysis (NMA). STUDY DESIGN AND SETTING: We consider evidence in an NMA to be potentially biased. Taking each pairwise contrast in turn, we use a structured series of threshold analyses to ask: (1) “How large would the bias in this evidence base have to be before it changed our decision?” and (2) “If the decision changed, what is the new recommendation?” We illustrate the method via two NMAs in which a Grading of Recommendations Assessment, Development and Evaluation (GRADE) assessment for NMAs has been implemented: weight loss and osteoporosis. RESULTS: Four of the weight-loss NMA estimates were assessed as “low” and six as “moderate” quality by GRADE; for osteoporosis, six were “low,” nine were “moderate,” and 1 was “high.” The threshold analysis suggests plausible bias in 3 of 10 estimates in the weight-loss network could have changed the treatment recommendation. For osteoporosis, plausible bias in 6 of 16 estimates could change the recommendation. There was no relation between plausible bias changing a treatment recommendation and the original GRADE assessments. CONCLUSIONS: Reliability judgments on individual NMA contrasts do not help decision makers understand whether a treatment recommendation is reliable. Threshold analysis reveals whether the final recommendation is robust against plausible degrees of bias in the data.
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spelling pubmed-51760102016-12-23 A threshold analysis assessed the credibility of conclusions from network meta-analysis Caldwell, Deborah M. Ades, A.E. Dias, Sofia Watkins, Sarah Li, Tianjing Taske, Nichole Naidoo, Bhash Welton, Nicky J. J Clin Epidemiol Original Article OBJECTIVE: To assess the reliability of treatment recommendations based on network meta-analysis (NMA). STUDY DESIGN AND SETTING: We consider evidence in an NMA to be potentially biased. Taking each pairwise contrast in turn, we use a structured series of threshold analyses to ask: (1) “How large would the bias in this evidence base have to be before it changed our decision?” and (2) “If the decision changed, what is the new recommendation?” We illustrate the method via two NMAs in which a Grading of Recommendations Assessment, Development and Evaluation (GRADE) assessment for NMAs has been implemented: weight loss and osteoporosis. RESULTS: Four of the weight-loss NMA estimates were assessed as “low” and six as “moderate” quality by GRADE; for osteoporosis, six were “low,” nine were “moderate,” and 1 was “high.” The threshold analysis suggests plausible bias in 3 of 10 estimates in the weight-loss network could have changed the treatment recommendation. For osteoporosis, plausible bias in 6 of 16 estimates could change the recommendation. There was no relation between plausible bias changing a treatment recommendation and the original GRADE assessments. CONCLUSIONS: Reliability judgments on individual NMA contrasts do not help decision makers understand whether a treatment recommendation is reliable. Threshold analysis reveals whether the final recommendation is robust against plausible degrees of bias in the data. Elsevier 2016-12 /pmc/articles/PMC5176010/ /pubmed/27430731 http://dx.doi.org/10.1016/j.jclinepi.2016.07.003 Text en © 2016 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Original Article
Caldwell, Deborah M.
Ades, A.E.
Dias, Sofia
Watkins, Sarah
Li, Tianjing
Taske, Nichole
Naidoo, Bhash
Welton, Nicky J.
A threshold analysis assessed the credibility of conclusions from network meta-analysis
title A threshold analysis assessed the credibility of conclusions from network meta-analysis
title_full A threshold analysis assessed the credibility of conclusions from network meta-analysis
title_fullStr A threshold analysis assessed the credibility of conclusions from network meta-analysis
title_full_unstemmed A threshold analysis assessed the credibility of conclusions from network meta-analysis
title_short A threshold analysis assessed the credibility of conclusions from network meta-analysis
title_sort threshold analysis assessed the credibility of conclusions from network meta-analysis
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5176010/
https://www.ncbi.nlm.nih.gov/pubmed/27430731
http://dx.doi.org/10.1016/j.jclinepi.2016.07.003
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