They are graphs with 1-specificity on the x-axis and sensitivity on the y-axis, in which each primary study contributes to a unique point defined by its sensitivity and specificity for a given threshold. 27 It is also possible to create Summary ROC (SROC) curves. The below example shows a paired forest plot made using mock data.
Moreover, the number of true positives, false positives, true negatives and false negatives are also reported, as well as, where appropriate, any covariates (for instance the type of diagnostic test used). These values are also listed in numerical form. These graphs thus show the means and confidence intervals for sensitivity/specificity for each of the selected primary studies. In the case of diagnostic test accuracy, two forest plots are presented side by side: one for sensitivity and the other for specificity. As for systematic reviews of effectiveness, forest plots can be performed. Results of diagnostic test accuracy systematic reviews can be graphically represented through two different major ways.
Options for summarizing and presenting data are discussed further below. meta-analysis, narrative synthesis, graphical representation, etc. the protocol should describe how the outcome data of the primary studies will be combined and reported, i.e.
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