Center for Clinical Epidemiology and Methodology (CCEM), Guangdong Second Provincial General Hospital, Guangzhou, China; Department of Health research methods, Evidence, and Impact (HEI), McMaster University, Hamilton, Ontario, Canada; St. Joseph's Healthcare Hamilton, McMaster University, Hamilton, Ontario, Canada.
Center for Clinical Epidemiology and Methodology (CCEM), Guangdong Second Provincial General Hospital, Guangzhou, China; School of Public Health, Southern Medical University, Guangzhou, China.
J Clin Epidemiol. 2020 Jan;117:89-98. doi: 10.1016/j.jclinepi.2019.09.021. Epub 2019 Oct 4.
Forest plots are an important graphical method in meta-analyses used to show results from individual studies and pooled analyses. Forest plots are easy and straightforward to understand because they provide tabular and graphical information about estimates of comparisons or associations, corresponding precision, and statistical significance. This visual representation also makes it easier to see variations between individual study results. Forest plots are widely used in not only systematic reviews and meta-analyses but also observational studies and clinical trials. In this study, we aimed to show readers the various uses of forest plots in displaying analysis results.
We used a tutorial type to show multiple uses of forest plots in meta-analyses, clinical trials, and observational studies according to the PICO (Population or Subgroup, Intervention or Exposure, Control, and Outcome) framework.
We introduced forest plots' structure, application, current practice, and research advances in health research. We provided some examples from the literature to show the various uses of forest plot-type graphics in health research including meta-analyses, clinical trials, and observational studies.
It is expected that our discussion of the current multiple uses of forest plots in meta-analyses, clinical trials, and observational studies provides a glimpse about their potential in displaying results in a way that makes comparisons between items easier.
森林图是荟萃分析中一种重要的图形方法，用于展示来自单个研究和汇总分析的结果。森林图易于理解，因为它们提供了关于比较或关联的估计值、相应的精度和统计显著性的表格和图形信息。这种直观的表示形式也更容易看出单个研究结果之间的差异。森林图不仅在系统评价和荟萃分析中广泛使用，在观察性研究和临床试验中也广泛使用。在这项研究中，我们旨在向读者展示森林图在显示分析结果方面的多种用途。
我们采用教程的形式，根据 PICO（人群或亚组、干预或暴露、对照和结局）框架，展示了森林图在荟萃分析、临床试验和观察性研究中的多种用途。
我们介绍了森林图的结构、应用、当前实践和在健康研究中的研究进展。我们提供了一些文献中的示例，展示了森林图类型图形在健康研究中的多种用途，包括荟萃分析、临床试验和观察性研究。
希望我们对森林图在荟萃分析、临床试验和观察性研究中的当前多种用途的讨论，能够让人们了解它们在以更易于比较的方式展示结果方面的潜力。
