Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2008 Nov 11:8:75.
doi: 10.1186/1471-2288-8-75.

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

Angel M Cronin  1 , Andrew J Vickers
Affiliations

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

Angel M Cronin et al. BMC Med Res Methodol. .

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.

PubMed Disclaimer

Figures

Figure 1
Figure 1
Example of data subject to verification bias.
See this image and copyright information in PMC

References

    1. Begg CB, Greenes RA. Assessment of diagnostic tests when disease verification is subject to selection bias. Biometrics. 1983;39:207–215. doi: 10.2307/2530820. - DOI - PubMed
    1. Gray R, Begg CB, Greenes RA. Construction of receiver operating characteristic curves when disease verification is subject to selection bias. Med Decis Making. 1984;4:151–164. doi: 10.1177/0272989X8400400204. - DOI - PubMed
    1. Merl T, Scholz M, Gerhardt P, Langer M, Laubenberger J, Weiss HD, Gehl HB, Wolf KJ, Ohnesorge I. Results of a prospective multicenter study for evaluation of the diagnostic quality of an open whole-body low-field MRI unit. A comparison with high-field MRI measured by the applicable gold standard. Eur J Radiol. 1999;30:43–53. doi: 10.1016/S0720-048X(98)00134-X. - DOI - PubMed
    1. Punglia RS, D'Amico AV, Catalona WJ, Roehl KA, Kuntz KM. Effect of verification bias on screening for prostate cancer by measurement of prostate-specific antigen. N Engl J Med. 2003;349:335–342. doi: 10.1056/NEJMoa021659. - DOI - PubMed
    1. Roger VL, Pellikka PA, Bell MR, Chow CW, Bailey KR, Seward JB. Sex and test verification bias. Impact on the diagnostic value of exercise echocardiography. Circulation. 1997;95:405–410. - PubMed

Publication types