title: Adjusting for partial verification or workup bias in meta-analyses of diagnostic accuracy studies.
abstract: A key requirement in the design of diagnostic accuracy studies is that all study participants receive both the test under evaluation and the reference standard test. For a variety of practical and ethical reasons, sometimes only a proportion of patients receive the reference standard, which can bias the accuracy estimates. Numerous methods have been described for correcting this partial verification bias or workup bias in individual studies. In this article, the authors describe a Bayesian method for obtaining adjusted results from a diagnostic meta-analysis when partial verification or workup bias is present in a subset of the primary studies. The method corrects for verification bias without having to exclude primary studies with verification bias, thus preserving the main advantages of a meta-analysis: increased precision and better generalizability. The results of this method are compared with the existing methods for dealing with verification bias in diagnostic meta-analyses. For illustration, the authors use empirical data from a systematic review of studies of the accuracy of the immunohistochemistry test for diagnosis of human epidermal growth factor receptor 2 status in breast cancer patients.
authors.affiliation: Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, P.O. Box 85500, 3508GA Utrecht, the Netherlands. j.degroot-17@umcutrecht.nl
authors.forename: Joris A H
authors.initials: JA
authors.lastname: de Groot
authors.forename: Nandini
authors.initials: N
authors.lastname: Dendukuri
authors.forename: Kristel J M
authors.initials: KJ
authors.lastname: Janssen
authors.forename: Johannes B
authors.initials: JB
authors.lastname: Reitsma
authors.forename: James
authors.initials: J
authors.lastname: Brophy
authors.forename: Lawrence
authors.initials: L
authors.lastname: Joseph
authors.forename: Patrick M M
authors.initials: PM
authors.lastname: Bossuyt
authors.forename: Karel G M
authors.initials: KG
authors.lastname: Moons
mesh_terms: D001499:Bayes Theorem; D015982:Bias; D001943:Breast Neoplasms / Q000378:metabolism; D003627:Data Interpretation, Statistical; D019937:Diagnostic Techniques and Procedures; D005260:Female; D006801:Humans; D015201:Meta-Analysis as Topic; D018719:Erb-b2 Receptor Tyrosine Kinases / Q000378:metabolism; D012015:Reference Standards; D012680:Sensitivity and Specificity
chemical_list: D018719:Erb-b2 Receptor Tyrosine Kinases; C508053:ERBB2 protein, human