Graphical enhancements to summary receiver operating characteristic plots to facilitate the analysis and reporting of meta‐analysis of diagnostic test accuracy data. (12th August 2020)

• Record Type: Journal Article
• Authors: Patel, Amit; Cooper, Nicola; Freeman, Suzanne; Sutton, Alex
• Other Names: Chaimani Anna guestEditor.; Nikolakopoulou Adriani guestEditor.
• Is Part Of: Research synthesis methods. Volume 12:Number 1(2021)
• Page Start: 34
• Page End: 44
• Publication Date: 2020-08-12
• Subjects: diagnostic test accuracy -- meta‐analysis -- received operating characteristic curves; Research -- Methodology -- Periodicals; Research -- Statistical methods -- Periodicals; 507.2
• DOI: 10.1002/jrsm.1439
• Languages: English
• ISSNs: 1759-2879

Abstract

Abstract : Diagnostic test accuracy (DTA) systematic reviews are conducted to summarize evidence on the accuracy of a diagnostic test including a critical evaluation of the primary studies. Where appropriate, the evidence is meta‐analyzed to obtain pooled estimates of effectiveness.In this study, we reviewed and critiqued three DTA guidance documents with respect to the graphical presentation of DTA meta‐analysis results. All three documents recommended the use of two forms of graphical presentation: (a) forest plots displaying meta‐analysis results for sensitivity (ie, the true positive rate) and specificity (ie, true negative rate) separately, and (b) Summary Receiver Operating Characteristic (SROC) curve to provide a global summary of test performance. Two primary shortcomings were identified: (a) lack of incorporation of quality assessment results into the main analysis and; (b) ambiguity with which the contribution of individual studies is represented on SROC curves. In response, two alternative graphical approaches were developed: A quality assessment enhanced SROC plot which displays the results from individual studies in the meta‐analysis with multiple indicators of quality assessed using QUADAS‐2; and A percentage study weights enhanced SROC plot which accurately portrays the percentage contribution each study makes to the meta‐analysis. The proposed enhanced SROC curves facilitate the exploration of DTA data, leading to a deeper understanding of the primary studies included in a DTA meta‐analysis including identifying reasons for between study heterogeneity and why specific study results may be divergent. Both plots can easily be produced in the free online interactive application, MetaDTA (https://crsu.shinyapps.io/dta_ma/ ).