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The effect direction plot revisited: Application of the 2019 Cochrane Handbook guidance on alternative synthesis methods

机译:重新审视效果方向情节:在替代合成方法上应用2019年Cochrane手册指导

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Effect direction (evidence to indicate improvement, deterioration, or no change in an outcome) can be used as a standardized metric which enables the synthesis of diverse effect measures in systematic reviews. The effect direction (ED) plot was developed to support the synthesis and visualization of effect direction data. Methods for the ED plot require updating in light of new Cochrane guidance on alternative synthesis methods. To update the ED plot, statistical significance was removed from the algorithm for within-study synthesis and use of a sign test was considered to examine whether patterns of ED across studies could be due to chance alone. The revised methods were applied to an existing Cochrane review of the health impacts of housing improvements. The revised ED plot provides a method of data visualization in synthesis without meta-analysis that incorporates information about study characteristics and study quality, using ED as a common metric, without relying on statistical significance to combine outcomes of single studies. The results of sign tests, when appropriate, suggest caution in over-interpreting apparent patterns in effect direction, especially when the number of included studies is small. The revised ED plot meets the need for alternative methods of synthesis and data visualization when meta-analysis is not possible, enabling a transparent link between the data and conclusions of a systematic review. ED plots may be particularly useful in reviews that incorporate nonrandomized studies, complex systems approaches, and diverse sources of evidence, due to the variety of study designs and outcomes in such reviews.
机译:效果方向(证据表明改进,恶化或未变化的结果)可用作标准化的指标,其能够在系统评价中合成各种效应措施。开发效果方向(ED)图以支持效果方向数据的合成和可视化。 ED PLOT的方法需要在替代合成方法的新的Cochrane指导中更新。为了更新ED图,从研究内的算法中除去统计显着性,并考虑使用标志测试来检查跨研究的ED模式是否可能是由于机会。修订后的方法适用于现有的Cochrane审查住房改善的健康影响。经修订的ED Plot提供了一种在合成中的数据可视化方法,无需荟萃分析,其中包含关于研究特征和研究质量的信息,使用ED作为常见的公制,而无需依赖于结合单一研究结果的统计学意义。当适当时,签署试验结果表明在效果方向上过度解释表观模式,特别是当包括研究的数量很小时。当不可能进行元分析时,修订的ED Plot符合替代合成方法和数据可视化方法,在系统审查的数据和结论之间启用透明的链接。由于在此类评论中的研究设计和结果的各种课程,Ed Plots在包含非扫描研究,复杂的系统方法和不同的证据来源的评论中可能特别有用。

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