Exploratory Network Meta Regression Analysis of Stroke Prevention in Atrial Fibrillation Fails to Identify Any Interactions with Treatment Effect.

<h4>Background</h4>Patients with atrial fibrillation are at a greater risk of stroke and therefore the main goal for treatment of patients with atrial fibrillation is to prevent stroke from occurring. There are a number of different stroke prevention treatments available to include warfa...

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Main Authors: Sarah Batson, Alex Sutton, Keith Abrams
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2016-01-01
Series:PLoS ONE
Online Access:https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0161864&type=printable
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author Sarah Batson
Alex Sutton
Keith Abrams
author_facet Sarah Batson
Alex Sutton
Keith Abrams
author_sort Sarah Batson
collection DOAJ
description <h4>Background</h4>Patients with atrial fibrillation are at a greater risk of stroke and therefore the main goal for treatment of patients with atrial fibrillation is to prevent stroke from occurring. There are a number of different stroke prevention treatments available to include warfarin and novel oral anticoagulants. Previous network meta-analyses of novel oral anticoagulants for stroke prevention in atrial fibrillation acknowledge the limitation of heterogeneity across the included trials but have not explored the impact of potentially important treatment modifying covariates.<h4>Objectives</h4>To explore potentially important treatment modifying covariates using network meta-regression analyses for stroke prevention in atrial fibrillation.<h4>Methods</h4>We performed a network meta-analysis for the outcome of ischaemic stroke and conducted an exploratory regression analysis considering potentially important treatment modifying covariates. These covariates included the proportion of patients with a previous stroke, proportion of males, mean age, the duration of study follow-up and the patients underlying risk of ischaemic stroke.<h4>Results</h4>None of the covariates explored impacted relative treatment effects relative to placebo. Notably, the exploration of 'study follow-up' as a covariate supported the assumption that difference in trial durations is unimportant in this indication despite the variation across trials in the network.<h4>Conclusion</h4>This study is limited by the quantity of data available. Further investigation is warranted, and, as justifying further trials may be difficult, it would be desirable to obtain individual patient level data (IPD) to facilitate an effort to relate treatment effects to IPD covariates in order to investigate heterogeneity. Observational data could also be examined to establish if there are potential trends elsewhere. The approach and methods presented have potentially wide applications within any indication as to highlight the potential benefit of extending decision problems to include additional comparators outside of those of primary interest to allow for the exploration of heterogeneity.
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spelling doaj-art-af77e3b9dc0b41c9a3ed4017a39eaa062025-01-24T05:31:14ZengPublic Library of Science (PLoS)PLoS ONE1932-62032016-01-01118e016186410.1371/journal.pone.0161864Exploratory Network Meta Regression Analysis of Stroke Prevention in Atrial Fibrillation Fails to Identify Any Interactions with Treatment Effect.Sarah BatsonAlex SuttonKeith Abrams<h4>Background</h4>Patients with atrial fibrillation are at a greater risk of stroke and therefore the main goal for treatment of patients with atrial fibrillation is to prevent stroke from occurring. There are a number of different stroke prevention treatments available to include warfarin and novel oral anticoagulants. Previous network meta-analyses of novel oral anticoagulants for stroke prevention in atrial fibrillation acknowledge the limitation of heterogeneity across the included trials but have not explored the impact of potentially important treatment modifying covariates.<h4>Objectives</h4>To explore potentially important treatment modifying covariates using network meta-regression analyses for stroke prevention in atrial fibrillation.<h4>Methods</h4>We performed a network meta-analysis for the outcome of ischaemic stroke and conducted an exploratory regression analysis considering potentially important treatment modifying covariates. These covariates included the proportion of patients with a previous stroke, proportion of males, mean age, the duration of study follow-up and the patients underlying risk of ischaemic stroke.<h4>Results</h4>None of the covariates explored impacted relative treatment effects relative to placebo. Notably, the exploration of 'study follow-up' as a covariate supported the assumption that difference in trial durations is unimportant in this indication despite the variation across trials in the network.<h4>Conclusion</h4>This study is limited by the quantity of data available. Further investigation is warranted, and, as justifying further trials may be difficult, it would be desirable to obtain individual patient level data (IPD) to facilitate an effort to relate treatment effects to IPD covariates in order to investigate heterogeneity. Observational data could also be examined to establish if there are potential trends elsewhere. The approach and methods presented have potentially wide applications within any indication as to highlight the potential benefit of extending decision problems to include additional comparators outside of those of primary interest to allow for the exploration of heterogeneity.https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0161864&type=printable
spellingShingle Sarah Batson
Alex Sutton
Keith Abrams
Exploratory Network Meta Regression Analysis of Stroke Prevention in Atrial Fibrillation Fails to Identify Any Interactions with Treatment Effect.
PLoS ONE
title Exploratory Network Meta Regression Analysis of Stroke Prevention in Atrial Fibrillation Fails to Identify Any Interactions with Treatment Effect.
title_full Exploratory Network Meta Regression Analysis of Stroke Prevention in Atrial Fibrillation Fails to Identify Any Interactions with Treatment Effect.
title_fullStr Exploratory Network Meta Regression Analysis of Stroke Prevention in Atrial Fibrillation Fails to Identify Any Interactions with Treatment Effect.
title_full_unstemmed Exploratory Network Meta Regression Analysis of Stroke Prevention in Atrial Fibrillation Fails to Identify Any Interactions with Treatment Effect.
title_short Exploratory Network Meta Regression Analysis of Stroke Prevention in Atrial Fibrillation Fails to Identify Any Interactions with Treatment Effect.
title_sort exploratory network meta regression analysis of stroke prevention in atrial fibrillation fails to identify any interactions with treatment effect
url https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0161864&type=printable
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AT alexsutton exploratorynetworkmetaregressionanalysisofstrokepreventioninatrialfibrillationfailstoidentifyanyinteractionswithtreatmenteffect
AT keithabrams exploratorynetworkmetaregressionanalysisofstrokepreventioninatrialfibrillationfailstoidentifyanyinteractionswithtreatmenteffect