A new method to address verification bias in studies of clinical screening tests: cervical cancer screening assays as an example

Abstract

Objectives: Studies to evaluate clinical screening tests often face the problem that the "gold standard" diagnostic approach is costly and/or invasive. It is therefore common to verify only a subset of negative screening tests using the gold standard method. However, undersampling the screen negatives can lead to substantial overestimation of the sensitivity and underestimation of the specificity of the diagnostic test. Our objective was to develop a simple and accurate statistical method to address this "verification bias."

Study design and setting: We developed a weighted generalized estimating equation approach to estimate, in a single model, the accuracy (eg, sensitivity/specificity) of multiple assays and simultaneously compare results between assays while addressing verification bias. This approach can be implemented using standard statistical software. Simulations were conducted to assess the proposed method. An example is provided using a cervical cancer screening trial that compared the accuracy of human papillomavirus and Pap tests, with histologic data as the gold standard.

Results: The proposed approach performed well in estimating and comparing the accuracy of multiple assays in the presence of verification bias.

Conclusion: The proposed approach is an easy to apply and accurate method for addressing verification bias in studies of multiple screening methods.

Keywords: Clinical screening tests; Positive and negative predictive values; Sensitivity; Specificity; Verification bias; Weighted generalized estimating equations.