TY - JOUR
T1 - A new method to address verification bias in studies of clinical screening tests
T2 - Cervical cancer screening assays as an example
AU - Xue, Xiaonan
AU - Kim, Mimi Y.
AU - Castle, Philip E.
AU - Strickler, Howard D.
N1 - Funding Information:
Funding: This work was supported by NCI R01 CA174634 and R01 CA85178 .
PY - 2014/3
Y1 - 2014/3
N2 - 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.
AB - 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.
KW - Clinical screening tests
KW - Positive and negative predictive values
KW - Sensitivity
KW - Specificity
KW - Verification bias
KW - Weighted generalized estimating equations
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U2 - 10.1016/j.jclinepi.2013.09.013
DO - 10.1016/j.jclinepi.2013.09.013
M3 - Article
C2 - 24332397
AN - SCOPUS:84894955959
SN - 0895-4356
VL - 67
SP - 343
EP - 353
JO - Journal of Chronic Diseases
JF - Journal of Chronic Diseases
IS - 3
ER -