Department of Population Health Sciences, University of Leicester, UK; NIHR Complex Reviews Support Unit, University of Leicester & University of Glasgow, Glasgow, UK.
Department of Population Health Sciences, University of Leicester, UK; NIHR Complex Reviews Support Unit, University of Leicester & University of Glasgow, Glasgow, UK.
J Clin Epidemiol. 2023 May;157:83-91. doi: 10.1016/j.jclinepi.2023.02.016. Epub 2023 Mar 3.
Network meta-analysis (NMA) is becoming a popular statistical tool for analyzing a network of evidence comparing more than two interventions. A particular advantage of NMA over pairwise meta-analysis is its ability to simultaneously compare multiple interventions including comparisons not previously trialed together, permitting intervention hierarchies to be created. Our aim was to develop a novel graphical display to aid interpretation of NMA to clinicians and decision-makers that incorporates ranking of interventions.
Current literature was searched, scrutinized, and provided direction for developing the novel graphical display. Ranking results were often found to be misinterpreted when presented alone and, to aid interpretation and effective communication to inform optimal decision-making, need to be displayed alongside other important aspects of the analysis including the evidence networks and relative intervention effect estimates.
Two new ranking visualizations were developed-the 'Litmus Rank-O-Gram' and the 'Radial SUCRA' plot-and embedded within a novel multipanel graphical display programmed within the MetaInsight application, with user feedback gained.
This display was designed to improve the reporting, and facilitate a holistic understanding, of NMA results. We believe uptake of the display would lead to better understanding of complex results and improve future decision-making.
网络荟萃分析（NMA）正成为一种分析比较两种以上干预措施的证据网络的流行统计工具。与两两荟萃分析相比，NMA 的一个特别优势是能够同时比较多种干预措施，包括以前未一起试验过的比较，从而可以创建干预层次结构。我们的目的是开发一种新的图形显示，以帮助临床医生和决策者解释 NMA，该显示包含对干预措施的排序。
对现有文献进行了搜索、仔细审查，并为开发新的图形显示提供了方向。当单独呈现排名结果时，常常发现其被误解，为了帮助解释和进行有效的沟通以告知最佳决策，需要与分析的其他重要方面一起显示，包括证据网络和相对干预效果估计。
开发了两种新的排名可视化方法-“石蕊排序图”和“径向 SUCRA 图”-并嵌入在 MetaInsight 应用程序内的一个新的多面板图形显示中，并获得了用户反馈。
该显示旨在改进 NMA 结果的报告，并促进对其的全面理解。我们相信，该显示的采用将导致对复杂结果的更好理解，并改善未来的决策。
