DTAmetasa: An R shiny application for meta-analysis of diagnostic test accuracy and sensitivity analysis of publication bias.
R shiny application
diagnostic test accuracy
meta-analysis
publication bias
sensitivity analysis
Journal
Research synthesis methods
ISSN: 1759-2887
Titre abrégé: Res Synth Methods
Pays: England
ID NLM: 101543738
Informations de publication
Date de publication:
Nov 2023
Nov 2023
Historique:
revised:
12
07
2023
received:
04
02
2023
accepted:
15
08
2023
medline:
8
11
2023
pubmed:
29
8
2023
entrez:
28
8
2023
Statut:
ppublish
Résumé
Meta-analysis of diagnostic test accuracy (DTA) is a powerful statistical method for synthesizing and evaluating the diagnostic capacity of medical tests and has been extensively used by clinical physicians and healthcare decision-makers. However, publication bias (PB) threatens the validity of meta-analysis of DTA. Some statistical methods have been developed to deal with PB in meta-analysis of DTA, but implementing these methods requires high-level statistical knowledge and programming skill. To assist non-technical users in running most routines in meta-analysis of DTA and handling with PB, we developed an interactive application, DTAmetasa. DTAmetasa is developed as a web-based graphical user interface based on the R shiny framework. It allows users to upload data and conduct meta-analysis of DTA by "point and click" operations. Moreover, DTAmetasa provides the sensitivity analysis of PB and presents the graphical results to evaluate the magnitude of the PB under various publication mechanisms. In this study, we introduce the functionalities of DTAmetasa and use the real-world meta-analysis to show its capacity for dealing with PB.
Types de publication
Meta-Analysis
Journal Article
Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
916-925Subventions
Organisme : Grant-in-Aid for Challenging Exploratory Research
ID : 16K12403
Organisme : Ministry of Education, Science, Sports and Technology of Japan
ID : 18H03208
Organisme : Ministry of Education, Science, Sports and Technology of Japan
ID : 16H06299
Informations de copyright
© 2023 John Wiley & Sons Ltd.
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