Statistical methods to correct for verification bias in diagnostic studies are inadequate when there are few false negatives: A simulation study Journal Article


Authors: Cronin, A. M.; Vickers, A. J.
Article Title: Statistical methods to correct for verification bias in diagnostic studies are inadequate when there are few false negatives: A simulation study
Abstract: Background. A common feature of diagnostic research is that results for a diagnostic gold standard are available primarily for patients who are positive for the test under investigation. Data from such studies are subject to what has been termed "verification bias". We evaluated statistical methods for verification bias correction when there are few false negatives. Methods. A simulation study was conducted of a screening study subject to verification bias. We compared estimates of the area-under-the-curve (AUC) corrected for verification bias varying both the rate and mechanism of verification. Results. In a single simulated data set, varying false negatives from 0 to 4 led to verification bias corrected AUCs ranging from 0.550 to 0.852. Excess variation associated with low numbers of false negatives was confirmed in simulation studies and by analyses of published studies that incorporated verification bias correction. The 2.5th - 97.5th centile range constituted as much as 60% of the possible range of AUCs for some simulations. Conclusion. Screening programs are designed such that there are few false negatives. Standard statistical methods for verification bias correction are inadequate in this circumstance. © 2008 Cronin and Vickers; licensee BioMed Central Ltd.
Keywords: area under the curve; diagnostic accuracy; laboratory diagnosis; sensitivity and specificity; prostate specific antigen; cancer screening; biopsy; prostate cancer; simulation; prostatic neoplasms; standard; statistical analysis; diagnostic value; prostate tumor; research; prediction and forecasting; predictive value of tests; scintiscanning; imaging; computer simulation; area under curve; diagnostic test; epidemiology; bias (epidemiology); screening test; single photon emission computer tomography; uterine cervical neoplasms; false negative reactions; coronary artery disease; uterine cervix tumor; disease activity; diagnostic tests, routine; systematic error
Journal Title: BMC Medical Research Methodology
Volume: 8
ISSN: 1471-2288
Publisher: Biomed Central Ltd  
Date Published: 2008-11-01
Start Page: 75
Language: English
DOI: 10.1186/1471-2288-8-75
PUBMED: 19014457
PROVIDER: scopus
PMCID: PMC2600821
DOI/URL:
Notes: --- - "Cited By (since 1996): 13" - "Export Date: 17 November 2011" - "Source: Scopus"
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MSK Authors
  1. Andrew J Vickers
    565 Vickers
  2. Angel M Cronin
    145 Cronin