Assessment of inverse publication bias in safety outcomes: an empirical analysis

Abstract Background The aims of this study were to assess the presence of inverse publication bias (IPB) in adverse events, evaluate the performance of visual examination, and explore the impact of considering effect direction in statistical tests for such assessments. Methods We conducted a cross-s...

Full description

Saved in:
Bibliographic Details
Main Authors: Xing Xing, Jianan Zhu, Linyu Shi, Chang Xu, Lifeng Lin
Format: Article
Language:English
Published: BMC 2024-10-01
Series:BMC Medicine
Subjects:
Online Access:https://doi.org/10.1186/s12916-024-03707-2
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1850203721534799872
author Xing Xing
Jianan Zhu
Linyu Shi
Chang Xu
Lifeng Lin
author_facet Xing Xing
Jianan Zhu
Linyu Shi
Chang Xu
Lifeng Lin
author_sort Xing Xing
collection DOAJ
description Abstract Background The aims of this study were to assess the presence of inverse publication bias (IPB) in adverse events, evaluate the performance of visual examination, and explore the impact of considering effect direction in statistical tests for such assessments. Methods We conducted a cross-sectional study using the SMART Safety, the largest dataset for evidence synthesis of adverse events. The visual assessment was performed using contour-enhanced funnel plots, trim-and-fill funnel plots, and sample-size-based funnel plots. Two authors conducted visual assessments of these plots independently, and their agreements were quantified by the kappa statistics. Additionally, IPB was quantitatively assessed using both the one- and two-sided Egger’s and Peters’ tests. Results In the SMART Safety dataset, we identified 277 main meta-analyses of safety outcomes with at least 10 individual estimates after dropping missing data. We found that about 13.7–16.2% of meta-analyses exhibited IPB according to the one-sided test results. The kappa statistics for the visual assessments roughly ranged from 0.3 to 0.5, indicating fair to moderate agreement. Using the one-sided Egger’s test, 57 out of 72 (79.2%) meta-analyses that initially showed significant IPB in the two-sided test changed to non-significant, while the remaining 15 (20.8%) meta-analyses changed from non-significant to significant. Conclusions Our findings provide supporting evidence of IPB in the SMART Safety dataset of adverse events. They also suggest the importance of researchers carefully accounting for the direction of statistical tests for IPB, as well as the challenges of assessing IPB using statistical methods, especially considering that the number of studies is typically small. Qualitative assessments may be a necessary supplement to gain a more comprehensive understanding of IPB.
format Article
id doaj-art-4a197845bb7246c488652709fdd18320
institution OA Journals
issn 1741-7015
language English
publishDate 2024-10-01
publisher BMC
record_format Article
series BMC Medicine
spelling doaj-art-4a197845bb7246c488652709fdd183202025-08-20T02:11:26ZengBMCBMC Medicine1741-70152024-10-012211910.1186/s12916-024-03707-2Assessment of inverse publication bias in safety outcomes: an empirical analysisXing Xing0Jianan Zhu1Linyu Shi2Chang Xu3Lifeng Lin4Department of Biostatistics, Johns Hopkins Bloomberg School of Public HealthDepartment of Biostatistics, School of Global Public Health, New York UniversityAbbVie IncProof of Concept Center, Eastern Hepatobiliary Surgery Hospital, Third Affiliated Hospital, Second Military Medical University, Naval Medical UniversityDepartment of Epidemiology and Biostatistics, University of ArizonaAbstract Background The aims of this study were to assess the presence of inverse publication bias (IPB) in adverse events, evaluate the performance of visual examination, and explore the impact of considering effect direction in statistical tests for such assessments. Methods We conducted a cross-sectional study using the SMART Safety, the largest dataset for evidence synthesis of adverse events. The visual assessment was performed using contour-enhanced funnel plots, trim-and-fill funnel plots, and sample-size-based funnel plots. Two authors conducted visual assessments of these plots independently, and their agreements were quantified by the kappa statistics. Additionally, IPB was quantitatively assessed using both the one- and two-sided Egger’s and Peters’ tests. Results In the SMART Safety dataset, we identified 277 main meta-analyses of safety outcomes with at least 10 individual estimates after dropping missing data. We found that about 13.7–16.2% of meta-analyses exhibited IPB according to the one-sided test results. The kappa statistics for the visual assessments roughly ranged from 0.3 to 0.5, indicating fair to moderate agreement. Using the one-sided Egger’s test, 57 out of 72 (79.2%) meta-analyses that initially showed significant IPB in the two-sided test changed to non-significant, while the remaining 15 (20.8%) meta-analyses changed from non-significant to significant. Conclusions Our findings provide supporting evidence of IPB in the SMART Safety dataset of adverse events. They also suggest the importance of researchers carefully accounting for the direction of statistical tests for IPB, as well as the challenges of assessing IPB using statistical methods, especially considering that the number of studies is typically small. Qualitative assessments may be a necessary supplement to gain a more comprehensive understanding of IPB.https://doi.org/10.1186/s12916-024-03707-2Adverse eventFunnel plotInverse publication biasPublication biasSystematic review
spellingShingle Xing Xing
Jianan Zhu
Linyu Shi
Chang Xu
Lifeng Lin
Assessment of inverse publication bias in safety outcomes: an empirical analysis
BMC Medicine
Adverse event
Funnel plot
Inverse publication bias
Publication bias
Systematic review
title Assessment of inverse publication bias in safety outcomes: an empirical analysis
title_full Assessment of inverse publication bias in safety outcomes: an empirical analysis
title_fullStr Assessment of inverse publication bias in safety outcomes: an empirical analysis
title_full_unstemmed Assessment of inverse publication bias in safety outcomes: an empirical analysis
title_short Assessment of inverse publication bias in safety outcomes: an empirical analysis
title_sort assessment of inverse publication bias in safety outcomes an empirical analysis
topic Adverse event
Funnel plot
Inverse publication bias
Publication bias
Systematic review
url https://doi.org/10.1186/s12916-024-03707-2
work_keys_str_mv AT xingxing assessmentofinversepublicationbiasinsafetyoutcomesanempiricalanalysis
AT jiananzhu assessmentofinversepublicationbiasinsafetyoutcomesanempiricalanalysis
AT linyushi assessmentofinversepublicationbiasinsafetyoutcomesanempiricalanalysis
AT changxu assessmentofinversepublicationbiasinsafetyoutcomesanempiricalanalysis
AT lifenglin assessmentofinversepublicationbiasinsafetyoutcomesanempiricalanalysis