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Reducing misclassification bias in cervical dysplasia risk factor analysis with p16-based diagnoses
Emily Meserve1, Michelle Berlin, Tomi Mori
1Departments of 1Pathology, 2Obstetrics & Gynecology, and 3Medical Informatics & Clinical Epidemiology at Oregon Health & Science University; and 4Pathology at Kaiser Permanente Northwest, Portland, OR.
Journal of Lower Genital Tract Disease
|March 18, 2014
Summary
p16-based diagnoses improve cervical cancer risk factor analysis accuracy compared to conventional HE staining. This enhanced accuracy strengthens risk estimates, particularly for factors like low family income, in high-grade dysplasia cases.
Area of Science:
- Gynecologic Pathology
- Cervical Cancer Screening
- Diagnostic Accuracy
Background:
- Conventional hematoxylin and eosin (HE) staining is the standard for cervical cancer risk factor analysis but has limited reproducibility and predictive value.
- Immunohistochemical staining using the neoplastic marker p16 offers improved diagnostic accuracy for cervical lesions.
Purpose of the Study:
- To evaluate if p16-based diagnoses significantly alter high-grade dysplasia (cervical intraepithelial neoplasia 2+) risk factor analysis compared to the HE standard.
- To assess the impact of p16 staining on the identification of risk factors for cervical intraepithelial neoplasia 2+.
Main Methods:
- Retrospective analysis of 358 cervical biopsy cases with at least 5 years of follow-up.
- Index and follow-up biopsies were immunostained for p16 and Ki-67, reviewed by blinded pathologists.
- Statistical analysis using chi-squared tests and logistic regression modeling.
Main Results:
- Clinically significant diagnostic errors were found in 22% of HE-based diagnoses.
- p16-based diagnoses strengthened the association between low family income and cervical intraepithelial neoplasia 2+ (OR=1.71) compared to HE (OR=1.12).
- Ki-67 staining did not significantly impact the results.
Conclusions:
- p16-based diagnoses can significantly influence the outcomes of cervical cancer risk factor analyses.
- The impact of p16 staining is more pronounced in smaller study cohorts.
- Utilizing p16 staining may enhance the precision of identifying risk factors for high-grade cervical dysplasia.
