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Quantifying Bias in Randomized Controlled Trials in Child Health: A Meta-Epidemiological Study

OBJECTIVE: To quantify bias related to specific methodological characteristics in child-relevant randomized controlled trials (RCTs). DESIGN: Meta-epidemiological study. DATA SOURCES: We identified systematic reviews containing a meta-analysis with 10–40 RCTs that were relevant to child health in th...

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Autores principales: Hartling, Lisa, Hamm, Michele P., Fernandes, Ricardo M., Dryden, Donna M., Vandermeer, Ben
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3913714/
https://www.ncbi.nlm.nih.gov/pubmed/24505351
http://dx.doi.org/10.1371/journal.pone.0088008
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author Hartling, Lisa
Hamm, Michele P.
Fernandes, Ricardo M.
Dryden, Donna M.
Vandermeer, Ben
author_facet Hartling, Lisa
Hamm, Michele P.
Fernandes, Ricardo M.
Dryden, Donna M.
Vandermeer, Ben
author_sort Hartling, Lisa
collection PubMed
description OBJECTIVE: To quantify bias related to specific methodological characteristics in child-relevant randomized controlled trials (RCTs). DESIGN: Meta-epidemiological study. DATA SOURCES: We identified systematic reviews containing a meta-analysis with 10–40 RCTs that were relevant to child health in the Cochrane Database of Systematic Reviews. DATA EXTRACTION: Two reviewers independently assessed RCTs using items in the Cochrane Risk of Bias tool and other study factors. We used meta-epidemiological methods to assess for differences in effect estimates between studies classified as high/unclear vs. low risk of bias. RESULTS: We included 287 RCTs from 17 meta-analyses. The proportion of studies at high/unclear risk of bias was: 79% sequence generation, 83% allocation concealment, 67% blinding of participants, 47% blinding of outcome assessment, 49% incomplete outcome data, 32% selective outcome reporting, 44% other sources of bias, 97% overall risk of bias, 56% funding, 35% baseline imbalance, 13% blocked randomization in unblinded trials, and 1% early stopping for benefit. We found no significant differences in effect estimates for studies that were high/unclear vs. low risk of bias for any of the risk of bias domains, overall risk of bias, or other study factors. CONCLUSIONS: We found no differences in effect estimates between studies based on risk of bias. A potential explanation is the number of trials included, in particular the small number of studies with low risk of bias. Until further evidence is available, reviewers should not exclude RCTs from systematic reviews and meta-analyses based solely on risk of bias particularly in the area of child health.
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spelling pubmed-39137142014-02-06 Quantifying Bias in Randomized Controlled Trials in Child Health: A Meta-Epidemiological Study Hartling, Lisa Hamm, Michele P. Fernandes, Ricardo M. Dryden, Donna M. Vandermeer, Ben PLoS One Research Article OBJECTIVE: To quantify bias related to specific methodological characteristics in child-relevant randomized controlled trials (RCTs). DESIGN: Meta-epidemiological study. DATA SOURCES: We identified systematic reviews containing a meta-analysis with 10–40 RCTs that were relevant to child health in the Cochrane Database of Systematic Reviews. DATA EXTRACTION: Two reviewers independently assessed RCTs using items in the Cochrane Risk of Bias tool and other study factors. We used meta-epidemiological methods to assess for differences in effect estimates between studies classified as high/unclear vs. low risk of bias. RESULTS: We included 287 RCTs from 17 meta-analyses. The proportion of studies at high/unclear risk of bias was: 79% sequence generation, 83% allocation concealment, 67% blinding of participants, 47% blinding of outcome assessment, 49% incomplete outcome data, 32% selective outcome reporting, 44% other sources of bias, 97% overall risk of bias, 56% funding, 35% baseline imbalance, 13% blocked randomization in unblinded trials, and 1% early stopping for benefit. We found no significant differences in effect estimates for studies that were high/unclear vs. low risk of bias for any of the risk of bias domains, overall risk of bias, or other study factors. CONCLUSIONS: We found no differences in effect estimates between studies based on risk of bias. A potential explanation is the number of trials included, in particular the small number of studies with low risk of bias. Until further evidence is available, reviewers should not exclude RCTs from systematic reviews and meta-analyses based solely on risk of bias particularly in the area of child health. Public Library of Science 2014-02-04 /pmc/articles/PMC3913714/ /pubmed/24505351 http://dx.doi.org/10.1371/journal.pone.0088008 Text en © 2014 Hartling et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Hartling, Lisa
Hamm, Michele P.
Fernandes, Ricardo M.
Dryden, Donna M.
Vandermeer, Ben
Quantifying Bias in Randomized Controlled Trials in Child Health: A Meta-Epidemiological Study
title Quantifying Bias in Randomized Controlled Trials in Child Health: A Meta-Epidemiological Study
title_full Quantifying Bias in Randomized Controlled Trials in Child Health: A Meta-Epidemiological Study
title_fullStr Quantifying Bias in Randomized Controlled Trials in Child Health: A Meta-Epidemiological Study
title_full_unstemmed Quantifying Bias in Randomized Controlled Trials in Child Health: A Meta-Epidemiological Study
title_short Quantifying Bias in Randomized Controlled Trials in Child Health: A Meta-Epidemiological Study
title_sort quantifying bias in randomized controlled trials in child health: a meta-epidemiological study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3913714/
https://www.ncbi.nlm.nih.gov/pubmed/24505351
http://dx.doi.org/10.1371/journal.pone.0088008
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