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
. 2022 Mar 18;22(1):70.
doi: 10.1186/s12874-021-01481-w.

Adjusting for verification bias in diagnostic accuracy measures when comparing multiple screening tests - an application to the IP1-PROSTAGRAM study

Emily Day  1 , David Eldred-Evans  2 , A Toby Prevost  3 , Hashim U Ahmed  2   4 , Francesca Fiorentino  5   6   7
Affiliations

Adjusting for verification bias in diagnostic accuracy measures when comparing multiple screening tests - an application to the IP1-PROSTAGRAM study

Emily Day et al. BMC Med Res Methodol. .

Abstract

Introduction: Novel screening tests used to detect a target condition are compared against either a reference standard or other existing screening methods. However, as it is not always possible to apply the reference standard on the whole population under study, verification bias is introduced. Statistical methods exist to adjust estimates to account for this bias. We extend common methods to adjust for verification bias when multiple tests are compared to a reference standard using data from a prospective double blind screening study for prostate cancer.

Methods: Begg and Greenes method and multiple imputation are extended to include the results of multiple screening tests which determine condition verification status. These two methods are compared to the complete case analysis using the IP1-PROSTAGRAM study data. IP1-PROSTAGRAM used a paired-cohort double-blind design to evaluate the use of imaging as alternative tests to screen for prostate cancer, compared to a blood test called prostate specific antigen (PSA). Participants with positive imaging (index) and/or PSA (control) underwent a prostate biopsy (reference standard).

Results: When comparing complete case results to Begg and Greenes and methods of multiple imputation there is a statistically significant increase in the specificity estimates for all screening tests. Sensitivity estimates remained similar across the methods, with completely overlapping 95% confidence intervals. Negative predictive value (NPV) estimates were higher when adjusting for verification bias, compared to complete case analysis, even though the 95% confidence intervals overlap. Positive predictive value (PPV) estimates were similar across all methods.

Conclusion: Statistical methods are required to adjust for verification bias in accuracy estimates of screening tests. Expanding Begg and Greenes method to include multiple screening tests can be computationally intensive, hence multiple imputation is recommended, especially as it can be modified for low prevalence of the target condition.

Keywords: Begg and Greenes; Multiple imputation; Sensitivity; Specificity; Verification bias.

PubMed Disclaimer

Conflict of interest statement

HU Ahmed reported receiving grants from Wellcome Trust, the BMA Foundation for Medical Research, and The Urology Foundation during the conduct of the study and grants and personal fees from Sophiris Biocorp, Sonacare Inc., and Boston Scientific (previously Galil and BTG) and grants from Trod Medical, Prostate Cancer UK charity, NIHR, MRC (UK), Cancer Research UK charity, and Imperial Health Charity outside the submitted work. D Eldred-Evans reported receiving grants from the BMA Foundation for Medical Research, The Urology Foundation, and the Royal College of Surgeons of England during the conduct of the study; grants from Imperial Health Charity outside the submitted work.

References

    1. Maxim LD, Niebo R, Utell MJ. Screening tests: a review with examples. Inhal Toxicol. 2014;26(13):811–828. doi: 10.3109/08958378.2014.955932. - DOI - PMC - PubMed
    1. Knottnerus JA, van Weel C. General introduction: evaluation of diagnostic procedures. In: The evidence base of clinical diagnosis. London: BMJ Books; 2002. pp. 1–18.
    1. Pepe MS. The Statistical Evaluation of Medical Tests for Classification and Prediction. Oxford University Press; 2003. p. 169.
    1. De Groot JAH, Janssen KJM, Zwinderman AH, et al. Correcting for partial verification bias: a comparison of methods. Ann Epidemiol. 2011;21:139–48. doi: 10.1016/j.annepidem.2010.10.004. - DOI - PubMed
    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

Publication types

Substances