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Nov, 2023;14 (6): 916-925.

DTAmetasa: An R shiny application for meta-analysis of diagnostic test accuracy and sensitivity analysis of publication bias.

Shosuke Mizutani, Yi Zhou, Yu-Shi Tian, Tatsuya Takagi, Tadayasu Ohkubo, Satoshi Hattori
Author Information
  1. Shosuke Mizutani: Graduate School of Pharmaceutical Sciences, Osaka University, Osaka, Japan.
  2. Yi Zhou: Beijing International Center for Mathematical Research, Peking University, Beijing, China. ORCID
  3. Yu-Shi Tian: Graduate School of Pharmaceutical Sciences, Osaka University, Osaka, Japan. ORCID
  4. Tatsuya Takagi: Graduate School of Pharmaceutical Sciences, Osaka University, Osaka, Japan. ORCID
  5. Tadayasu Ohkubo: Graduate School of Pharmaceutical Sciences, Osaka University, Osaka, Japan.
  6. Satoshi Hattori: Department of Biomedical Statistics, Graduate School of Medicine, Osaka University, Osaka, Japan. ORCID
PMID: 37640914 DOI: 10.1002/jrsm.1666

Abstract

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.

Keywords

R shiny application diagnostic test accuracy meta-analysis publication bias sensitivity analysis

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Grants

  1. 16K12403/Grant-in-Aid for Challenging Exploratory Research
  2. 18H03208/Ministry of Education, Science, Sports and Technology of Japan
  3. 16H06299/Ministry of Education, Science, Sports and Technology of Japan

MeSH Term

Publication Bias
Diagnostic Tests, Routine
Meta-Analysis Journal Article Review
Article has an altmetric score of 1

Word Cloud

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