Diagnostic test accuracy network meta-analysis methods: a scoping review and empirical assessment

Areti Angeliki Veroniki, Sofia Tsokani, Ridhi Agarwal, Eirini Pagkalidou, Gerta Rücker, Dimitris Mavridis, Yemisi Takwoingi

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Abstract

Objectives: To (a) identify methodological and application papers reporting a model developed specifically for diagnostic test accuracy network meta-analysis (DTA-NMA) or a hierarchical meta-regression method for comparing at least three index tests; (b) review and summarize the characteristics of the methods and the application papers; and (c) compare DTA-NMA and hierarchical meta-regression methods empirically. Study Design and Setting: We performed a scoping review and searched major databases until March 3rd, 2021. We assessed the characteristics of the identified methods, conducted a descriptive analysis of characteristics of the application articles, and applied the DTA-NMA and meta-regression methods to the available data. Results: We included 49 articles (plus one companion report), of which nine were methodological (describing 11 DTA-NMA methods) and 40 were application papers (data available for 32 DTA-NMAs). Our results showed a steep increase in recent years in DTA-NMA publications. DTA-NMA models may lead to different results. Although sensitivity estimates were comparable between meta-regression and DTA-NMA models, specificity estimates were higher in meta-regression. Conclusion: The choice of a DTA-NMA model will depend on the available data, including the use of different thresholds for test positivity, different study designs, and software familiarity. Selection between the methods may impact on the NMA results, especially for specificity.

Original languageEnglish
Pages (from-to)86-96
Number of pages11
JournalJournal of Clinical Epidemiology
Volume146
Early online date16 Feb 2022
DOIs
Publication statusPublished - Jun 2022

Bibliographical note

Funding Information:
Funding: This review received no funding. ST and DM were funded from the European Union's Horizon 2020 [No. 754936 ]. GR was funded by the German Research Foundation (DFG) , grant number RU 1747/1-2 . YT is funded by a UK National Institute for Health Research (NIHR) Postdoctoral Fellowship , and is supported by the NIHR Birmingham Biomedical Research Centre. The views expressed are those of the authors and not necessarily those of the NHS, NIHR, or the Department of Health and Social Care.

Publisher Copyright:
© 2022

Keywords

  • Accuracy
  • Diagnostic test
  • Indirect comparison
  • Network meta-analysis
  • Sensitivity
  • Specificity

ASJC Scopus subject areas

  • Epidemiology

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