A proposed framework to guide evidence synthesis practice for meta-analysis with zero-events studies
ObjectiveIn evidence synthesis practice, researchers often face the problem of how to deal with zero-events. Inappropriately dealing with zero-events studies may lead to research waste and mislead healthcare practice. We propose a framework to guide researchers to better deal with zero-events in met...
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| مؤلفون آخرون: | , , , |
| التنسيق: | article |
| منشور في: |
2021
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| الوصول للمادة أونلاين: | http://dx.doi.org/10.1016/j.jclinepi.2021.02.012 https://www.sciencedirect.com/science/article/pii/S0895435621000494?v=s5 http://hdl.handle.net/10576/17795 |
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| الملخص: | ObjectiveIn evidence synthesis practice, researchers often face the problem of how to deal with zero-events. Inappropriately dealing with zero-events studies may lead to research waste and mislead healthcare practice. We propose a framework to guide researchers to better deal with zero-events in meta-analysis. Study Design and SettingWe used two dimensions, one with respect to the total events count across all studies in the comparative arms in a meta-analysis, and a second with respect to whether included studies have single or both arms with zero-events, to establish the framework for the classification of meta-analysis with zero-events studies. A dataset from Cochrane systematic reviews was used to evaluate the classification. ResultsThe proposed framework classifies meta-analysis with zero-events studies into six subtypes. The classification matched well to the large real-world dataset. The applicability of existing methods for zero-events were then presented under each meta-analysis subtype based on this framework, with a 5-step principle to help researchers in evidence synthesis practice. ConclusionsThe proposed framework should be considered by researchers when making decisions on the selection of the synthesis methods in a meta-analysis. It also provides a reasonable basis for the development of methodological guidelines to deal with zero-events in meta-analysis. |
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