Abstract
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.
Highlights
Identified methods were classified into four main groups: methods employed when there is a missing gold standard; correction methods; 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
Various 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)
Summary
Before a new medical test can be introduced into clinical practice, it should be evaluated for analytical validity (does the test work in the laboratory?), clinical validity (does the test work in the patient population of interest?) and clinical utility (is the test useful–can it lead to improvement in health outcomes?) [1, 2]. Other common measures are predictive values, likelihood values, overall accuracy [8, 9], receiver operating characteristic (ROC) curve, area under the ROC curve (AUROC) [10], ROC surface, and volume under the ROC surface (VUS) [11,12,13]. These measures are obtained by comparing the index test results with the results of the best currently available test for diagnosing the same target condition in the same participants; both tests are supposedly applied to all participants of the study [14]. The term “bias” in this review is defined as the difference between the estimated value and the true value of the parameter of interest [16]
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