Reducing misclassification bias in cervical dysplasia risk factor analysis with p16-based diagnoses

Emily Meserve, Michelle Berlin, Motomi (Tomi) Mori, Robert Krum, Terry Morgan

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4 Citations (Scopus)

Abstract

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.

Original languageEnglish (US)
Pages (from-to)266-272
Number of pages7
JournalJournal of Lower Genital Tract Disease
Volume18
Issue number3
DOIs
StatePublished - 2014

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Uterine Cervical Dysplasia
Statistical Factor Analysis
Hematoxylin
Eosine Yellowish-(YS)
Biopsy
Papanicolaou Test
Cervical Intraepithelial Neoplasia
Odds Ratio
Confidence Intervals
Vaginal Smears
Diagnostic Errors
Uterine Cervical Neoplasms
Logistic Models
Staining and Labeling

Keywords

  • cervical cancer
  • epidemiology
  • misclassification bias
  • p16 immunohistochemistry

ASJC Scopus subject areas

  • Obstetrics and Gynecology
  • Medicine(all)

Cite this

@article{860faa194e5a4466b972c4cfb77aef13,
title = "Reducing misclassification bias in cervical dysplasia risk factor analysis with p16-based diagnoses",
abstract = "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.",
keywords = "cervical cancer, epidemiology, misclassification bias, p16 immunohistochemistry",
author = "Emily Meserve and Michelle Berlin and Mori, {Motomi (Tomi)} and Robert Krum and Terry Morgan",
year = "2014",
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language = "English (US)",
volume = "18",
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journal = "Journal of Lower Genital Tract Disease",
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TY - JOUR

T1 - Reducing misclassification bias in cervical dysplasia risk factor analysis with p16-based diagnoses

AU - Meserve, Emily

AU - Berlin, Michelle

AU - Mori, Motomi (Tomi)

AU - Krum, Robert

AU - Morgan, Terry

PY - 2014

Y1 - 2014

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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