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Accounting for nonignorable verification bias in assessment of diagnostic tests.

Publication ,  Journal Article
Kosinski, AS; Barnhart, HX
Published in: Biometrics
March 2003

A "gold" standard test, providing definitive verification of disease status, may be quite invasive or expensive. Current technological advances provide less invasive, or less expensive, diagnostic tests. Ideally, a diagnostic test is evaluated by comparing it with a definitive gold standard test. However, the decision to perform the gold standard test to establish the presence or absence of disease is often influenced by the results of the diagnostic test, along with other measured, or not measured, risk factors. If only data from patients who received the gold standard test were used to assess the test performance, the commonly used measures of diagnostic test performance--sensitivity and specificity--are likely to be biased. Sensitivity would often be higher, and specificity would be lower, than the true values. This bias is called verification bias. Without adjustment for verification bias, one may possibly introduce into the medical practice a diagnostic test with apparent, but not truly, high sensitivity. In this article, verification bias is treated as a missing covariate problem. We propose a flexible modeling and computational framework for evaluating the performance of a diagnostic test, with adjustment for nonignorable verification bias. The presented computational method can be utilized with any software that can repetitively use a logistic regression module. The approach is likelihood-based, and allows use of categorical or continuous covariates. An explicit formula for the observed information matrix is presented, so that one can easily compute standard errors of estimated parameters. The methodology is illustrated with a cardiology data example. We perform a sensitivity analysis of the dependency of verification selection process on disease.

Duke Scholars

Published In

Biometrics

DOI

ISSN

0006-341X

Publication Date

March 2003

Volume

59

Issue

1

Start / End Page

163 / 171

Location

England

Related Subject Headings

  • Tomography, Emission-Computed, Single-Photon
  • Statistics & Probability
  • Sensitivity and Specificity
  • Selection Bias
  • Middle Aged
  • Male
  • Logistic Models
  • Likelihood Functions
  • Humans
  • Female
 

Citation

APA
Chicago
ICMJE
MLA
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Kosinski, A. S., & Barnhart, H. X. (2003). Accounting for nonignorable verification bias in assessment of diagnostic tests. Biometrics, 59(1), 163–171. https://doi.org/10.1111/1541-0420.00019
Kosinski, Andrzej S., and Huiman X. Barnhart. “Accounting for nonignorable verification bias in assessment of diagnostic tests.Biometrics 59, no. 1 (March 2003): 163–71. https://doi.org/10.1111/1541-0420.00019.
Kosinski AS, Barnhart HX. Accounting for nonignorable verification bias in assessment of diagnostic tests. Biometrics. 2003 Mar;59(1):163–71.
Kosinski, Andrzej S., and Huiman X. Barnhart. “Accounting for nonignorable verification bias in assessment of diagnostic tests.Biometrics, vol. 59, no. 1, Mar. 2003, pp. 163–71. Pubmed, doi:10.1111/1541-0420.00019.
Kosinski AS, Barnhart HX. Accounting for nonignorable verification bias in assessment of diagnostic tests. Biometrics. 2003 Mar;59(1):163–171.
Journal cover image

Published In

Biometrics

DOI

ISSN

0006-341X

Publication Date

March 2003

Volume

59

Issue

1

Start / End Page

163 / 171

Location

England

Related Subject Headings

  • Tomography, Emission-Computed, Single-Photon
  • Statistics & Probability
  • Sensitivity and Specificity
  • Selection Bias
  • Middle Aged
  • Male
  • Logistic Models
  • Likelihood Functions
  • Humans
  • Female