TY - JOUR
T1 - Reducing misclassification bias in cervical dysplasia risk factor analysis with p16-based diagnoses
AU - Meserve, Emily
AU - Berlin, Michelle
AU - Mori, Tomi
AU - Krum, Robert
AU - Morgan, Terry K.
N1 - Copyright:
Copyright 2014 Elsevier B.V., All rights reserved.
PY - 2014/7
Y1 - 2014/7
N2 - OBJECTIVE: Conventional hematoxylin and eosin (HE)-based diagnoses have been the reference standard for cervical cancer risk factor analyses. However, this HE-based method is known to have modest interobserver reproducibility and only moderate predictive value. In contrast, more recent immunohistochemical- based diagnoses using the neoplastic marker p16 are known to improve diagnostic accuracy. Our objective was to test whether p16-based diagnoses would significantly affect high-grade dysplasia (cervical intraepithelial neoplasia 2+) risk factor analysis compared with the current reference standard (HE). MATERIALS AND METHODS: Retrospective cohort of 500 index cases were randomly selected from a series of more than 5,000 cervical biopsies performed at Kaiser Permanente Northwest from 1997 to 2003 after a patient's first abnormal cervical Pap smear (positive for atypical squamous cells of undetermined significance). Subjects were subsequently excluded if they did not have at least 5 years of clinical follow-up, including cervical biopsies, or 3 reproducibly negative Pap smears. This yielded 358 cases for risk factor analysis. The index biopsies and all follow-up biopsies were immunostained for p16 and the proliferation marker Ki-67, which were then independently reviewed by 2 pathologists blinded to clinical outcomes. Data were analyzed by χ test and logistic regression modeling. RESULTS: We observed clinically significant diagnostic errors in 22% of index biopsies. Improved accuracy using p16 strengthened the risk estimate of low family income for cervical intraepithelial neoplasia 2+ (odds ratio = 1.71, 95% confidence interval = 1.09-2.63) compared with HE-based diagnoses (odds ratio = 1.12, 95% confidence interval = 0.72-1.72). The addition of Ki-67 staining did not significantly influence these results. CONCLUSIONS: p16-based diagnoses may affect the power of risk factor analysis, especially when using small cohorts.
AB - OBJECTIVE: Conventional hematoxylin and eosin (HE)-based diagnoses have been the reference standard for cervical cancer risk factor analyses. However, this HE-based method is known to have modest interobserver reproducibility and only moderate predictive value. In contrast, more recent immunohistochemical- based diagnoses using the neoplastic marker p16 are known to improve diagnostic accuracy. Our objective was to test whether p16-based diagnoses would significantly affect high-grade dysplasia (cervical intraepithelial neoplasia 2+) risk factor analysis compared with the current reference standard (HE). MATERIALS AND METHODS: Retrospective cohort of 500 index cases were randomly selected from a series of more than 5,000 cervical biopsies performed at Kaiser Permanente Northwest from 1997 to 2003 after a patient's first abnormal cervical Pap smear (positive for atypical squamous cells of undetermined significance). Subjects were subsequently excluded if they did not have at least 5 years of clinical follow-up, including cervical biopsies, or 3 reproducibly negative Pap smears. This yielded 358 cases for risk factor analysis. The index biopsies and all follow-up biopsies were immunostained for p16 and the proliferation marker Ki-67, which were then independently reviewed by 2 pathologists blinded to clinical outcomes. Data were analyzed by χ test and logistic regression modeling. RESULTS: We observed clinically significant diagnostic errors in 22% of index biopsies. Improved accuracy using p16 strengthened the risk estimate of low family income for cervical intraepithelial neoplasia 2+ (odds ratio = 1.71, 95% confidence interval = 1.09-2.63) compared with HE-based diagnoses (odds ratio = 1.12, 95% confidence interval = 0.72-1.72). The addition of Ki-67 staining did not significantly influence these results. CONCLUSIONS: p16-based diagnoses may affect the power of risk factor analysis, especially when using small cohorts.
KW - cervical cancer
KW - epidemiology
KW - misclassification bias
KW - p16 immunohistochemistry
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U2 - 10.1097/LGT.0000000000000001
DO - 10.1097/LGT.0000000000000001
M3 - Article
C2 - 24633165
AN - SCOPUS:84903819457
SN - 1089-2591
VL - 18
SP - 266
EP - 272
JO - Journal of Lower Genital Tract Disease
JF - Journal of Lower Genital Tract Disease
IS - 3
ER -