Identifying null meta-analyses that are ripe for updating
<p>Abstract</p> <p>Background</p> <p>As an increasingly large number of meta-analyses are published, quantitative methods are needed to help clinicians and systematic review teams determine when meta-analyses are not up to date.</p> <p>Methods</p> <...
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doaj-2d02dbaaf674453d9bd32771c56eb4572020-11-24T23:53:12ZengBMCBMC Medical Research Methodology1471-22882003-07-01311310.1186/1471-2288-3-13Identifying null meta-analyses that are ripe for updatingFang ManchunBarrowman Nicholas JSampson MargaretMoher David<p>Abstract</p> <p>Background</p> <p>As an increasingly large number of meta-analyses are published, quantitative methods are needed to help clinicians and systematic review teams determine when meta-analyses are not up to date.</p> <p>Methods</p> <p>We propose new methods for determining when non-significant meta-analytic results might be overturned, based on a prediction of the number of participants required in new studies. To guide decision making, we introduce the <it>"new participant ratio"</it>, the ratio of the actual number of participants in new studies to the predicted number required to obtain statistical significance. A simulation study was conducted to study the performance of our methods and a real meta-analysis provides further evidence.</p> <p>Results</p> <p>In our three simulation configurations, our diagnostic test for determining whether a meta-analysis is out of date had sensitivity of 55%, 62%, and 49% with corresponding specificity of 85%, 80%, and 90% respectively.</p> <p>Conclusions</p> <p>Simulations suggest that our methods are able to detect out-of-date meta-analyses. These quick and approximate methods show promise for use by systematic review teams to help decide whether to commit the considerable resources required to update a meta-analysis. Further investigation and evaluation of the methods is required before they can be recommended for general use.</p> http://www.biomedcentral.com/1471-2288/3/13 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Fang Manchun Barrowman Nicholas J Sampson Margaret Moher David |
spellingShingle |
Fang Manchun Barrowman Nicholas J Sampson Margaret Moher David Identifying null meta-analyses that are ripe for updating BMC Medical Research Methodology |
author_facet |
Fang Manchun Barrowman Nicholas J Sampson Margaret Moher David |
author_sort |
Fang Manchun |
title |
Identifying null meta-analyses that are ripe for updating |
title_short |
Identifying null meta-analyses that are ripe for updating |
title_full |
Identifying null meta-analyses that are ripe for updating |
title_fullStr |
Identifying null meta-analyses that are ripe for updating |
title_full_unstemmed |
Identifying null meta-analyses that are ripe for updating |
title_sort |
identifying null meta-analyses that are ripe for updating |
publisher |
BMC |
series |
BMC Medical Research Methodology |
issn |
1471-2288 |
publishDate |
2003-07-01 |
description |
<p>Abstract</p> <p>Background</p> <p>As an increasingly large number of meta-analyses are published, quantitative methods are needed to help clinicians and systematic review teams determine when meta-analyses are not up to date.</p> <p>Methods</p> <p>We propose new methods for determining when non-significant meta-analytic results might be overturned, based on a prediction of the number of participants required in new studies. To guide decision making, we introduce the <it>"new participant ratio"</it>, the ratio of the actual number of participants in new studies to the predicted number required to obtain statistical significance. A simulation study was conducted to study the performance of our methods and a real meta-analysis provides further evidence.</p> <p>Results</p> <p>In our three simulation configurations, our diagnostic test for determining whether a meta-analysis is out of date had sensitivity of 55%, 62%, and 49% with corresponding specificity of 85%, 80%, and 90% respectively.</p> <p>Conclusions</p> <p>Simulations suggest that our methods are able to detect out-of-date meta-analyses. These quick and approximate methods show promise for use by systematic review teams to help decide whether to commit the considerable resources required to update a meta-analysis. Further investigation and evaluation of the methods is required before they can be recommended for general use.</p> |
url |
http://www.biomedcentral.com/1471-2288/3/13 |
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