A comparison of meta-analytic methods for synthesizing evidence from explanatory and pragmatic trials

Abstract Background The pragmatic–explanatory continuum indicator summary version 2 (PRECIS-2) tool has recently been developed to classify randomized clinical trials (RCTs) as pragmatic or explanatory based on their design characteristics. Given that treatment effects in explanatory trials may be g...

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Main Authors: Tolulope T. Sajobi, Guowei Li, Oluwagbohunmi Awosoga, Meng Wang, Bijoy K. Menon, Michael D. Hill, Lehana Thabane
Format: Article
Language:English
Published: BMC 2018-01-01
Series:Systematic Reviews
Subjects:
Online Access:http://link.springer.com/article/10.1186/s13643-017-0668-3
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spelling doaj-4fc6f431fddd48ec84b175cdde0fbfbe2020-11-24T21:18:25ZengBMCSystematic Reviews2046-40532018-01-01711810.1186/s13643-017-0668-3A comparison of meta-analytic methods for synthesizing evidence from explanatory and pragmatic trialsTolulope T. Sajobi0Guowei Li1Oluwagbohunmi Awosoga2Meng Wang3Bijoy K. Menon4Michael D. Hill5Lehana Thabane6Department of Community Health Sciences and O’Brien Institute for Public Health, University of CalgaryDepartment of Health Research Methods, Evidence, and Impact, McMaster UniversityFaculty of Health Sciences, University of LethbridgeDepartment of Clinical Neurosciences, University of CalgaryDepartment of Clinical Neurosciences and Hotchkiss Brain Institute, University of CalgaryDepartment of Clinical Neurosciences and Hotchkiss Brain Institute, University of CalgaryDepartment of Health Research Methods, Evidence, and Impact, McMaster UniversityAbstract Background The pragmatic–explanatory continuum indicator summary version 2 (PRECIS-2) tool has recently been developed to classify randomized clinical trials (RCTs) as pragmatic or explanatory based on their design characteristics. Given that treatment effects in explanatory trials may be greater than those obtained in pragmatic trials, conventional meta-analytic approaches may not accurately account for the heterogeneity among the studies and may result in biased treatment effect estimates. This study investigates if the incorporation of PRECIS-2 classification of published trials can improve the estimation of overall intervention effects in meta-analysis. Methods Using data from 31 published trials of intervention aimed at reducing obesity in children, we evaluated the utility of incorporating PRECIS-2 ratings of published trials into meta-analysis of intervention effects in clinical trials. Specifically, we compared random-effects meta-analysis, stratified meta-analysis, random-effects meta-regression, and mixture random-effects meta-regression methods for estimating overall pooled intervention effects. Results Our analyses revealed that mixture meta-regression models that incorporate PRECIS-2 classification as covariate resulted in a larger pooled effect size (ES) estimate (ES = − 1.01, 95%CI = [− 1.52, − 0.43]) than conventional random-effects meta-analysis (ES = − 0.15, 95%CI = [− 0.23, − 0.08]). Conclusions In addition to the original intent of PRECIS-2 tool of aiding researchers in their choice of trial design, PRECIS-2 tool is useful for explaining between study variations in systematic review and meta-analysis of published trials. We recommend that researchers adopt mixture meta-regression methods when synthesizing evidence from explanatory and pragmatic trials.http://link.springer.com/article/10.1186/s13643-017-0668-3Meta-analysisPRECIS-2Obesity interventionsRandomized controlled trialsSystematic review
collection DOAJ
language English
format Article
sources DOAJ
author Tolulope T. Sajobi
Guowei Li
Oluwagbohunmi Awosoga
Meng Wang
Bijoy K. Menon
Michael D. Hill
Lehana Thabane
spellingShingle Tolulope T. Sajobi
Guowei Li
Oluwagbohunmi Awosoga
Meng Wang
Bijoy K. Menon
Michael D. Hill
Lehana Thabane
A comparison of meta-analytic methods for synthesizing evidence from explanatory and pragmatic trials
Systematic Reviews
Meta-analysis
PRECIS-2
Obesity interventions
Randomized controlled trials
Systematic review
author_facet Tolulope T. Sajobi
Guowei Li
Oluwagbohunmi Awosoga
Meng Wang
Bijoy K. Menon
Michael D. Hill
Lehana Thabane
author_sort Tolulope T. Sajobi
title A comparison of meta-analytic methods for synthesizing evidence from explanatory and pragmatic trials
title_short A comparison of meta-analytic methods for synthesizing evidence from explanatory and pragmatic trials
title_full A comparison of meta-analytic methods for synthesizing evidence from explanatory and pragmatic trials
title_fullStr A comparison of meta-analytic methods for synthesizing evidence from explanatory and pragmatic trials
title_full_unstemmed A comparison of meta-analytic methods for synthesizing evidence from explanatory and pragmatic trials
title_sort comparison of meta-analytic methods for synthesizing evidence from explanatory and pragmatic trials
publisher BMC
series Systematic Reviews
issn 2046-4053
publishDate 2018-01-01
description Abstract Background The pragmatic–explanatory continuum indicator summary version 2 (PRECIS-2) tool has recently been developed to classify randomized clinical trials (RCTs) as pragmatic or explanatory based on their design characteristics. Given that treatment effects in explanatory trials may be greater than those obtained in pragmatic trials, conventional meta-analytic approaches may not accurately account for the heterogeneity among the studies and may result in biased treatment effect estimates. This study investigates if the incorporation of PRECIS-2 classification of published trials can improve the estimation of overall intervention effects in meta-analysis. Methods Using data from 31 published trials of intervention aimed at reducing obesity in children, we evaluated the utility of incorporating PRECIS-2 ratings of published trials into meta-analysis of intervention effects in clinical trials. Specifically, we compared random-effects meta-analysis, stratified meta-analysis, random-effects meta-regression, and mixture random-effects meta-regression methods for estimating overall pooled intervention effects. Results Our analyses revealed that mixture meta-regression models that incorporate PRECIS-2 classification as covariate resulted in a larger pooled effect size (ES) estimate (ES = − 1.01, 95%CI = [− 1.52, − 0.43]) than conventional random-effects meta-analysis (ES = − 0.15, 95%CI = [− 0.23, − 0.08]). Conclusions In addition to the original intent of PRECIS-2 tool of aiding researchers in their choice of trial design, PRECIS-2 tool is useful for explaining between study variations in systematic review and meta-analysis of published trials. We recommend that researchers adopt mixture meta-regression methods when synthesizing evidence from explanatory and pragmatic trials.
topic Meta-analysis
PRECIS-2
Obesity interventions
Randomized controlled trials
Systematic review
url http://link.springer.com/article/10.1186/s13643-017-0668-3
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