It is also expected that when evaluating the diagnostic accuracy of a medical test, the participants undertake both the index and reference tests within a short time-period if not simultaneously. Classical method of evaluating the diagnostic accuracy of a medical test with binary test result and dichotomized disease status.
The term “bias” in this review is defined as the difference between the estimated value and the true value of the parameter of interest. This means that the gold standard perfectly discriminates between participants with or without the target conditions and provides unbiased estimates of the diagnostic accuracy measure of the index test as describe in Fig 1. The reference standard could be a gold standard (GS), with sensitivity and specificity equal to 100%. The test employed as the benchmark to evaluate the index test is called the reference standard. 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. Other common measures are predictive values, likelihood values, overall accuracy, receiver operating characteristic (ROC) curve, area under the ROC curve (AUROC), ROC surface, and volume under the ROC surface (VUS). those with the disease) and specificity (the proportion of participants correctly identified by the index as not having the target condition) are basic measures of the diagnostic accuracy of a test. sensitivity and specificity) may inform what role the index test (the new test under evaluation) plays in the diagnostic pathway is it a triage, add-on or replacement test? Sensitivity (the proportion of participants correctly identified by the index test as having the target condition e.g. Clinical validity studies, also called diagnostic accuracy studies, evaluate the test’s accuracy in discriminating between patients with or without the target condition (disease). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Ĭompeting interests: The authors have declared that no competing interest exist.īefore 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?). The views expressed are those of the authors and not necessarily those of the NIHR, the NHS or the Department of Health and Social Care. The view and opinions expressed are those of the authors and do not necessary reflect those of the NIHR Newcastle In Vitro Diagnostics Co-operative, Newcastle University and Newcastle upon Tyne NHS Foundation Trust, the NHS or Newcastle Research Academy. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.ĭata Availability: All relevant data are within the manuscript and its supporting information files.įunding: This work is supported by the Newcastle University Research Excellence the School of Mathematics, Statistics and Physics Newcastle University the Institute of Health & Society Newcastle University and the National Institute for Health Research (NIHR). Received: JAccepted: SeptemPublished: October 11, 2019Ĭopyright: © 2019 Umemneku Chikere et al. PLoS ONE 14(10):Įditor: Gianni Virgili, Universita degli Studi di Firenze, ITALY Citation: Umemneku Chikere CM, Wilson K, Graziadio S, Vale L, Allen AJ (2019) Diagnostic test evaluation methodology: A systematic review of methods employed to evaluate diagnostic tests in the absence of gold standard – An update.
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