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When we shouldn’t borrow information from an existing network of trials for planning a new trial

Introduction: To achieve higher power or increased precision for a new trial, methods based on updating network meta-analysis (NMA) have been proposed by researchers. However, this approach could potentially lead to misinterpreted results and misstated conclusions. This work aims to investigate the...

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Autores principales: Ye, Fangshu, Wang, Chong, O’Connor, Annette M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10176253/
https://www.ncbi.nlm.nih.gov/pubmed/37188261
http://dx.doi.org/10.3389/fphar.2023.1157708
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author Ye, Fangshu
Wang, Chong
O’Connor, Annette M.
author_facet Ye, Fangshu
Wang, Chong
O’Connor, Annette M.
author_sort Ye, Fangshu
collection PubMed
description Introduction: To achieve higher power or increased precision for a new trial, methods based on updating network meta-analysis (NMA) have been proposed by researchers. However, this approach could potentially lead to misinterpreted results and misstated conclusions. This work aims to investigate the potential inflation of type I error risk when a new trial is conducted only when, based on a p-value of the comparison in the existing network, a “promising” difference between two treatments is noticed. Methods: We use simulations to evaluate the scenarios of interest. In particular, a new trial is to be conducted independently or depending on the results from previous NMA in various scenarios. Three analysis methods are applied to each simulation scenario: with the existing network, sequential analysis and without the existing network. Results: For the scenario that the new trial will be conducted only when a promising finding (p-value [Formula: see text] ) is indicated by the existing network, the type I error risk increased dramatically (38.5% in our example data) when analyzed with the existing network and sequential analysis. The type I error is controlled at 5% when analyzing the new trial without the existing network. Conclusion: If the intention is to combine a trial result with an existing network of evidence, or if it is expected that the trial will eventually be included in a network meta-analysis, then the decision that a new trial is performed should not depend on a statistically “promising” finding indicated by the existing network.
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spelling pubmed-101762532023-05-13 When we shouldn’t borrow information from an existing network of trials for planning a new trial Ye, Fangshu Wang, Chong O’Connor, Annette M. Front Pharmacol Pharmacology Introduction: To achieve higher power or increased precision for a new trial, methods based on updating network meta-analysis (NMA) have been proposed by researchers. However, this approach could potentially lead to misinterpreted results and misstated conclusions. This work aims to investigate the potential inflation of type I error risk when a new trial is conducted only when, based on a p-value of the comparison in the existing network, a “promising” difference between two treatments is noticed. Methods: We use simulations to evaluate the scenarios of interest. In particular, a new trial is to be conducted independently or depending on the results from previous NMA in various scenarios. Three analysis methods are applied to each simulation scenario: with the existing network, sequential analysis and without the existing network. Results: For the scenario that the new trial will be conducted only when a promising finding (p-value [Formula: see text] ) is indicated by the existing network, the type I error risk increased dramatically (38.5% in our example data) when analyzed with the existing network and sequential analysis. The type I error is controlled at 5% when analyzing the new trial without the existing network. Conclusion: If the intention is to combine a trial result with an existing network of evidence, or if it is expected that the trial will eventually be included in a network meta-analysis, then the decision that a new trial is performed should not depend on a statistically “promising” finding indicated by the existing network. Frontiers Media S.A. 2023-04-27 /pmc/articles/PMC10176253/ /pubmed/37188261 http://dx.doi.org/10.3389/fphar.2023.1157708 Text en Copyright © 2023 Ye, Wang and O’Connor. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Pharmacology
Ye, Fangshu
Wang, Chong
O’Connor, Annette M.
When we shouldn’t borrow information from an existing network of trials for planning a new trial
title When we shouldn’t borrow information from an existing network of trials for planning a new trial
title_full When we shouldn’t borrow information from an existing network of trials for planning a new trial
title_fullStr When we shouldn’t borrow information from an existing network of trials for planning a new trial
title_full_unstemmed When we shouldn’t borrow information from an existing network of trials for planning a new trial
title_short When we shouldn’t borrow information from an existing network of trials for planning a new trial
title_sort when we shouldn’t borrow information from an existing network of trials for planning a new trial
topic Pharmacology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10176253/
https://www.ncbi.nlm.nih.gov/pubmed/37188261
http://dx.doi.org/10.3389/fphar.2023.1157708
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