Defining the exit meta-analysis

绘图(图形) 荟萃分析 计算机科学 判别式 趋同(经济学) 索引(排版) 理论(学习稳定性) 数据科学 风险分析(工程) 运筹学 统计 人工智能 机器学习 数学 医学 经济 万维网 经济增长 内科学
作者
Jazeel Abdulmajeed,Luis Furuya‐Kanamori,Tawanda Chivese,Chang Xu,Lukman Thalib,Suhail A.R. Doi
出处
期刊:JBI evidence synthesis [Lippincott Williams & Wilkins]
标识
DOI:10.11124/jbies-24-00155
摘要

Introduction: In recent decades, clinical research has seen significant advancements, both in the generation and synthesis of evidence through meta-analyses. Despite these methodological advancements, there is a growing concern about the accumulation of repetitive and redundant literature, potentially contributing to research waste. This highlights the necessity for a mechanism to determine when a meta-analysis has conclusively addressed a research question, signaling no further need for additional studies—a concept we term an “exit” meta-analysis. Methods: We introduced a convergence index, the Doi-Abdulmajeed Trial Stability (DAts) index, and a convergence plot to determine the exit status of a meta-analysis. The performance of DAts was examined through simulation and applied to two real-world meta-analyses. Results: The DAts index and convergence plot demonstrate highly effective discriminative ability across varying study scenarios. This represents the first attempt to define an exit meta-analysis using a quantitative measurement of stability (as opposed to sufficiency) and its corresponding plot. The application to real-world scenarios further validated the utility of DAts and the convergence plot in identifying a conclusive (exit) meta-analyses. Conclusion: The new development of DAts and the convergence plot provide a promising tool for investigating the conclusiveness of meta-analyses. By identifying an exit status for meta-analysis, the scientific community may be equipped to make better-informed decisions on the continuation of research on a specific topic, thereby preventing research waste and focusing efforts on areas with unresolved questions.
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