Should studies with no events in both arms be excluded in evidence synthesis?
Author | Chang, Xu |
Author | Furuya-Kanamori, Luis |
Author | Islam, Nazmul |
Author | Doi, Suhail A. |
Available date | 2023-02-21T05:50:33Z |
Publication Date | 2022-11-30 |
Publication Name | Contemporary Clinical Trials |
Identifier | http://dx.doi.org/10.1016/j.cct.2022.106962 |
Citation | Xu C, Furuya-Kanamori L, Islam N, Doi SA. Should studies with no events in both arms be excluded in evidence synthesis?. Contemp Clin Trials. 2022;122:106962. doi:10.1016/j.cct.2022.106962 |
ISSN | 15517144 |
Abstract | ObjectivesIn safety assessment, studies with no events are a frequent occurrence when conducting meta-analyses. The current approach in meta-analysis is to exclude double-zero studies from the synthesis. In this study, we compared the performance of excluding and including double-zero studies. MethodsA simulation with 5000 iterations was conducted based on the real-world dataset from Cochrane reviews. The true distribution of the rare events rather than normal distribution for the effects were used in the data generating mechanism to simulate aggregate meta-analysis data. We used Doi's inverse variance heterogeneity (IVhet) model for the meta-analyses with continuity correction (of 0.5) to include double-zero studies and used the odds ratio effect size. The performance of including versus excluding double-zero studies were then compared. ResultsGenerally, there was much larger mean squared error when double zero studies were excluded than when double-zero studies were included. The coverage when studies were excluded rapidly deteriorates as heterogeneity increased, while remained at or above the nominal level when double-zero studies were included. When there were very few double-zero studies, the performances was almost the same when including or excluding these studies. Subgroup analysis showed that, even for meta-analyses with unbalanced sample size across the two arms, including double-zero studies improved performance compared to when they were excluded. ConclusionsIncluding double-zero studies in meta-analysis improved performance substantively when compared to excluding them, especially when the proportion of double-zero studies was large. Continuity correction with use of the IVhet model is therefore a good solution to deal with double-zero studies and should be considered in future meta-analyses. |
Sponsor | This work was made possible by the National Natural Science Foundation of China (72204003) and program grant #NPRP-BSRA01-0406-210030 from the Qatar National Research Fund (a member of Qatar Foundation). Luis Furuya-Kanamori was supported by an Australian National Health and Medical Research Council Fellowship (APP1158469). The findings herein reflect the work, and are solely the responsibility of the authors. The funding bodies had no role in any process of the study (i.e., study design, analysis, interpretation of data, writing of the report, and decision to submit the article for publication). |
Language | en |
Publisher | Elsevier |
Subject | Meta-analysis Double-zero studies Continuity correction IVhet |
Type | Article |
Volume Number | 122 |
ESSN | 1559-2030 |
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