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Lookup NU author(s): Chinyereugo Umemneku Chikere, Professor Kevin Wilson, Dr Sara Graziadio, Professor Luke ValeORCiD, Dr Joy AllenORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
ObjectiveTo systematically review methods developed and employed to evaluate the diagnostic accuracy of medical test when there is a missing or no gold standard.Study design and settingsArticles that proposed or applied any methods to evaluate the diagnostic accuracy of medical test(s) in the absence of gold standard were reviewed. The protocol for this review was registered in PROSPERO (CRD42018089349).ResultsIdentified methods were classified into four main groups: methods employed when there is a missing gold standard; correction methods (which make adjustment for an imperfect reference standard with known diagnostic accuracy measures); methods employed to evaluate a medical test using multiple imperfect reference standards; and other methods, like agreement studies, and a mixed group of alternative study designs. Fifty-one statistical methods were identified from the review that were developed to evaluate medical test(s) when the true disease status of some participants is unverified with the gold standard. Seven correction methods were identified and four methods were identified to evaluate medical test(s) using multiple imperfect reference standards. Flow-diagrams were developed to guide the selection of appropriate methods.ConclusionVarious methods have been proposed to evaluate medical test(s) in the absence of a gold standard for some or all participants in a diagnostic accuracy study. These methods depend on the availability of the gold standard, its’ application to the participants in the study and the availability of alternative reference standard(s). The clinical application of some of these methods, especially methods developed when there is missing gold standard is however limited. This may be due to the complexity of these methods and/or a disconnection between the fields of expertise of those who develop (e.g. mathematicians) and those who employ the methods (e.g. clinical researchers). This review aims to help close this gap with our classification and guidance tools.
Author(s): Umemneku Chikere CM, Wilson K, Graziadio S, Vale L, Allen AJ
Publication type: Article
Publication status: Published
Journal: PLoS ONE
Year: 2019
Volume: 14
Issue: 10
Online publication date: 11/10/2019
Acceptance date: 29/09/2019
Date deposited: 14/10/2019
ISSN (electronic): 1932-6203
Publisher: Public Library of Science
URL: https://doi.org/10.1371/journal.pone.0223832
DOI: 10.1371/journal.pone.0223832
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