How individual participant data meta-analyses have influenced trial design, conduct, and analysis
Identifieur interne : 002849 ( Ncbi/Curation ); précédent : 002848; suivant : 002850How individual participant data meta-analyses have influenced trial design, conduct, and analysis
Auteurs : Jayne F. Tierney [Royaume-Uni] ; Jean-Pierre Pignon [France] ; Francois Gueffyier [France] ; Mike Clarke [Royaume-Uni] ; Lisa Askie ; Claire L. Vale [Royaume-Uni] ; Sarah Burdett [Royaume-Uni]Source :
- Journal of Clinical Epidemiology [ 0895-4356 ] ; 2015.
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- KwdFr :
- MESH :
English descriptors
- KwdEn :
- MESH :
Abstract
To demonstrate how individual participant data (IPD) meta-analyses have impacted directly on the design and conduct of trials and highlight other advantages IPD might offer.
Potential examples of the impact of IPD meta-analyses on trials were identified at an international workshop, attended by individuals with experience in the conduct of IPD meta-analyses and knowledge of trials in their respective clinical areas. Experts in the field who did not attend were asked to provide any further examples. We then examined relevant trial protocols, publications, and Web sites to verify the impacts of the IPD meta-analyses. A subgroup of workshop attendees sought further examples and identified other aspects of trial design and conduct that may inform IPD meta-analyses.
We identified 52 examples of IPD meta-analyses thought to have had a direct impact on the design or conduct of trials. After screening relevant trial protocols and publications, we identified 28 instances where IPD meta-analyses had clearly impacted on trials. They have influenced the selection of comparators and participants, sample size calculations, analysis and interpretation of subsequent trials, and the conduct and analysis of ongoing trials, sometimes in ways that would not possible with systematic reviews of aggregate data. We identified additional potential ways that IPD meta-analyses could be used to influence trials.
IPD meta-analysis could be better used to inform the design, conduct, analysis, and interpretation of trials.
Url:
DOI: 10.1016/j.jclinepi.2015.05.024
PubMed: 26186982
PubMed Central: 4635379
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Lisa Askie<affiliation><nlm:aff id="aff6">NHMRC Clinical Trials Centre, ABN 15 211 513 464, Locked Bag 77, Camperdown, NSW 1450 Australia</nlm:aff>
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Le document en format XML
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<front><div type="abstract" xml:lang="en"><sec><title>Objectives</title>
<p>To demonstrate how individual participant data (IPD) meta-analyses have impacted directly on the design and conduct of trials and highlight other advantages IPD might offer.</p>
</sec>
<sec><title>Study Design and Setting</title>
<p>Potential examples of the impact of IPD meta-analyses on trials were identified at an international workshop, attended by individuals with experience in the conduct of IPD meta-analyses and knowledge of trials in their respective clinical areas. Experts in the field who did not attend were asked to provide any further examples. We then examined relevant trial protocols, publications, and Web sites to verify the impacts of the IPD meta-analyses. A subgroup of workshop attendees sought further examples and identified other aspects of trial design and conduct that may inform IPD meta-analyses.</p>
</sec>
<sec><title>Results</title>
<p>We identified 52 examples of IPD meta-analyses thought to have had a direct impact on the design or conduct of trials. After screening relevant trial protocols and publications, we identified 28 instances where IPD meta-analyses had clearly impacted on trials. They have influenced the selection of comparators and participants, sample size calculations, analysis and interpretation of subsequent trials, and the conduct and analysis of ongoing trials, sometimes in ways that would not possible with systematic reviews of aggregate data. We identified additional potential ways that IPD meta-analyses could be used to influence trials.</p>
</sec>
<sec><title>Conclusions</title>
<p>IPD meta-analysis could be better used to inform the design, conduct, analysis, and interpretation of trials.</p>
</sec>
</div>
</front>
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