In studies of diagnostic accuracy, the performance of an index test is assessed by verifying its results against those of a reference standard. If verification of index-test results by the preferred reference standard can be performed only in a subset of subjects, an alternative reference test could be given to the remainder. The drawback of this so-called differential-verification design is that the second reference test is often of lesser quality, or defines the target condition in a different way. Incorrectly treating results of the 2 reference standards as equivalent will lead to differential-verification bias. The Bayesian methods presented in this paper use a single model to (1) acknowledge the different nature of the 2 reference standards and (2) make simultaneous inferences about the population prevalence and the sensitivity, specificity, and predictive values of the index test with respect to both reference tests, in relation to latent disease status. We illustrate this approach using data from a study on the accuracy of the elbow extension test for diagnosis of elbow fractures in patients with elbow injury, using either radiography or follow-up as reference standards.
From the aJulius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands; bDivision of Clinical Epidemiology, McGill University, Montreal, Quebec, Canada; and cDepartment of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Center, Amsterdam, The Netherlands.
Submitted 7 May 2010; accepted 14 September 2010; posted 12 January 2011.
Supported by The Netherlands Organization for Scientific Research (project 9120.8004 and 918.10.615).
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Correspondence: Joris A. H. de Groot, Julius Center for Health Sciences and Primary care, UMC Utrecht, PO Box 85500, 3508 GA Utrecht, The Netherlands. Email: J.email@example.com or www.juliuscenter.nl.