Stepwise-Hierarchical Pooled Analysis for Synergistic Interpretation of Meta-analyses Involving Randomized and Observational Studies: Methodology Development

BackgroundThe necessity of including observational studies in meta-analyses has been discussed in the literature, but a synergistic analysis method for combining randomized and observational studies has not been reported. Observational studies differ in validity depending on...

Full description

Bibliographic Details
Main Authors: In-Soo Shin, Chai Hong Rim
Format: Article
Language:English
Published: JMIR Publications 2021-09-01
Series:Journal of Medical Internet Research
Online Access:https://www.jmir.org/2021/9/e29642
_version_ 1797735760370073600
author In-Soo Shin
Chai Hong Rim
author_facet In-Soo Shin
Chai Hong Rim
author_sort In-Soo Shin
collection DOAJ
description BackgroundThe necessity of including observational studies in meta-analyses has been discussed in the literature, but a synergistic analysis method for combining randomized and observational studies has not been reported. Observational studies differ in validity depending on the degree of the confounders’ influence. Combining interpretations may be challenging, especially if the statistical directions are similar but the magnitude of the pooled results are different between randomized and observational studies (the ”gray zone”). ObjectiveTo overcome these hindrances, in this study, we aim to introduce a logical method for clinical interpretation of randomized and observational studies. MethodsWe designed a stepwise-hierarchical pooled analysis method to analyze both distribution trends and individual pooled results by dividing the included studies into at least three stages (eg, all studies, balanced studies, and randomized studies). ResultsAccording to the model, the validity of a hypothesis is mostly based on the pooled results of randomized studies (the highest stage). Ascending patterns in which effect size and statistical significance increase gradually with stage strengthen the validity of the hypothesis; in this case, the effect size of the observational studies is lower than that of the true effect (eg, because of the uncontrolled effect of negative confounders). Descending patterns in which decreasing effect size and statistical significance gradually weaken the validity of the hypothesis suggest that the effect size and statistical significance of the observational studies is larger than the true effect (eg, because of researchers’ bias). ConclusionsWe recommend using the stepwise-hierarchical pooled analysis approach for meta-analyses involving randomized and observational studies.
first_indexed 2024-03-12T13:03:46Z
format Article
id doaj.art-b487b08225b24563983a9014f4756fba
institution Directory Open Access Journal
issn 1438-8871
language English
last_indexed 2024-03-12T13:03:46Z
publishDate 2021-09-01
publisher JMIR Publications
record_format Article
series Journal of Medical Internet Research
spelling doaj.art-b487b08225b24563983a9014f4756fba2023-08-28T18:59:56ZengJMIR PublicationsJournal of Medical Internet Research1438-88712021-09-01239e2964210.2196/29642Stepwise-Hierarchical Pooled Analysis for Synergistic Interpretation of Meta-analyses Involving Randomized and Observational Studies: Methodology DevelopmentIn-Soo Shinhttps://orcid.org/0000-0001-7535-3511Chai Hong Rimhttps://orcid.org/0000-0001-7431-4588 BackgroundThe necessity of including observational studies in meta-analyses has been discussed in the literature, but a synergistic analysis method for combining randomized and observational studies has not been reported. Observational studies differ in validity depending on the degree of the confounders’ influence. Combining interpretations may be challenging, especially if the statistical directions are similar but the magnitude of the pooled results are different between randomized and observational studies (the ”gray zone”). ObjectiveTo overcome these hindrances, in this study, we aim to introduce a logical method for clinical interpretation of randomized and observational studies. MethodsWe designed a stepwise-hierarchical pooled analysis method to analyze both distribution trends and individual pooled results by dividing the included studies into at least three stages (eg, all studies, balanced studies, and randomized studies). ResultsAccording to the model, the validity of a hypothesis is mostly based on the pooled results of randomized studies (the highest stage). Ascending patterns in which effect size and statistical significance increase gradually with stage strengthen the validity of the hypothesis; in this case, the effect size of the observational studies is lower than that of the true effect (eg, because of the uncontrolled effect of negative confounders). Descending patterns in which decreasing effect size and statistical significance gradually weaken the validity of the hypothesis suggest that the effect size and statistical significance of the observational studies is larger than the true effect (eg, because of researchers’ bias). ConclusionsWe recommend using the stepwise-hierarchical pooled analysis approach for meta-analyses involving randomized and observational studies.https://www.jmir.org/2021/9/e29642
spellingShingle In-Soo Shin
Chai Hong Rim
Stepwise-Hierarchical Pooled Analysis for Synergistic Interpretation of Meta-analyses Involving Randomized and Observational Studies: Methodology Development
Journal of Medical Internet Research
title Stepwise-Hierarchical Pooled Analysis for Synergistic Interpretation of Meta-analyses Involving Randomized and Observational Studies: Methodology Development
title_full Stepwise-Hierarchical Pooled Analysis for Synergistic Interpretation of Meta-analyses Involving Randomized and Observational Studies: Methodology Development
title_fullStr Stepwise-Hierarchical Pooled Analysis for Synergistic Interpretation of Meta-analyses Involving Randomized and Observational Studies: Methodology Development
title_full_unstemmed Stepwise-Hierarchical Pooled Analysis for Synergistic Interpretation of Meta-analyses Involving Randomized and Observational Studies: Methodology Development
title_short Stepwise-Hierarchical Pooled Analysis for Synergistic Interpretation of Meta-analyses Involving Randomized and Observational Studies: Methodology Development
title_sort stepwise hierarchical pooled analysis for synergistic interpretation of meta analyses involving randomized and observational studies methodology development
url https://www.jmir.org/2021/9/e29642
work_keys_str_mv AT insooshin stepwisehierarchicalpooledanalysisforsynergisticinterpretationofmetaanalysesinvolvingrandomizedandobservationalstudiesmethodologydevelopment
AT chaihongrim stepwisehierarchicalpooledanalysisforsynergisticinterpretationofmetaanalysesinvolvingrandomizedandobservationalstudiesmethodologydevelopment