Institute of Tropical Medicine Antwerp
Foundation of Public Utility

Bayesian meta-analysis of diagnostic tests allowing for imperfect reference standards

DSpace/Manakin Repository

Show simple item record

dc.contributor.author Menten, J. en_US
dc.contributor.author Boelaert, M. en_US
dc.contributor.author Lesaffre, E. en_US
dc.date.accessioned 2014-09-25T13:39:26Z
dc.date.available 2014-09-25T13:39:26Z
dc.date.issued 2013 en_US
dc.identifier.issn 0277-6715 en_US
dc.identifier.doi http://dx.doi.org/10.1002/sim.5959 en_US
dc.identifier.other ITG-C1A; ITG-H2A; MULTI; DCS; U-CTU; DPH; U-ECTD; JIF; DOI; Abstract; UPD56 en_US
dc.identifier.uri http://hdl.handle.net/10390/7633
dc.description.abstract There is an increasing interest in meta-analyses of rapid diagnostic tests (RDTs) for infectious diseases. To avoid spectrum bias, these meta-analyses should focus on phase IV studies performed in the target population. For many infectious diseases, these target populations attend primary health care centers in resource-constrained settings where it is difficult to perform gold standard diagnostic tests. As a consequence, phase IV diagnostic studies often use imperfect reference standards, which may result in biased meta-analyses of the diagnostic accuracy of novel RDTs. We extend the standard bivariate model for the meta-analysis of diagnostic studies to correct for differing and imperfect reference standards in the primary studies and to accommodate data from studies that try to overcome the absence of a true gold standard through the use of latent class analysis. Using Bayesian methods, improved estimates of sensitivity and specificity are possible, especially when prior information is available on the diagnostic accuracy of the reference test. In this analysis, the deviance information criterion can be used to detect conflicts between the prior information and observed data. When applying the model to a dataset of the diagnostic accuracy of an RDT for visceral leishmaniasis, the standard meta-analytic methods appeared to underestimate the specificity of the RDT. Copyright (c) 2013 John Wiley and Sons, Ltd. en_US
dc.language English en_US
dc.subject Protozoal diseases en_US
dc.subject Visceral en_US
dc.subject Leishmaniasis en_US
dc.subject Kala azar en_US
dc.subject Leishmania donovani en_US
dc.subject Vectors en_US
dc.subject Sandflies en_US
dc.subject Phlebotomus argentipes en_US
dc.subject Diagnosis en_US
dc.subject Rapid diagnostic tests en_US
dc.subject Meta-analysis en_US
dc.subject Bias en_US
dc.subject Reference values en_US
dc.subject Standards en_US
dc.subject Diagnostic errors en_US
dc.subject Accuracy en_US
dc.subject Data analysis en_US
dc.subject Methodology en_US
dc.subject Specificity en_US
dc.subject Sensitivity en_US
dc.subject Mathematical modeling en_US
dc.title Bayesian meta-analysis of diagnostic tests allowing for imperfect reference standards en_US
dc.type Article en_US
dc.citation.issue 30 en_US
dc.citation.jtitle Statistics in Medicine en_US
dc.citation.volume 32 en_US
dc.citation.pages 5398-5413 en_US
dc.identifier.pmid http://www.ncbi.nlm.nih.gov/pubmed/24003003 en_US
dc.citation.jabbreviation Stat Med en_US


Files in this item

Files Size Format View

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record