TY - JOUR
T1 - Adjusting for Differential-verification Bias in Diagnostic-accuracy Studies A Bayesian Approach
AU - de Groot, Joris A. H.
AU - Dendukuri, Nandini
AU - Janssen, Kristel J. M.
AU - Reitsma, Johannes B.
AU - Bossuyt, Patrick M. M.
AU - Moons, Karel G. M.
PY - 2011
Y1 - 2011
N2 - 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
AB - 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
U2 - https://doi.org/10.1097/EDE.0b013e318207fc5c
DO - https://doi.org/10.1097/EDE.0b013e318207fc5c
M3 - Article
C2 - 21228702
SN - 1044-3983
VL - 22
SP - 234
EP - 241
JO - Epidemiology (Cambridge, Mass.)
JF - Epidemiology (Cambridge, Mass.)
IS - 2
ER -