Increased cervical cancer risk associated with extended screening intervals after negative human papillomavirus test results: Bayesian risk estimates using the Pittsburgh Cervical Cancer Screening Model

Change of Practice Patterns Following an Educational Comment on Reports of Benign-Appearing Endometrial Cells in Papanicolaou Tests

OBJECTIVES

Since the publication of our study demonstrating high negative predictive values (>99% for women in their 40s) of benign-appearing endometrial cells (nEMCs), we have begun to include an educational comment in Papanicolaou (Pap) test reports with nEMCs that recommends routine periodic screening for asymptomatic premenopausal women (APW). The current study evaluated how the inclusion of this comment has affected clinical practice patterns at our institution.

METHODS

The 2017 to 2019 database identified 175 reports containing the educational comment in women aged 45 to 54 years with a follow-up time of 11 to 37 months. Data, including age, menopause status, symptoms, imaging, and outcome, were collected. The procedure rate and the impact of clinical modifiers were assessed.

RESULTS

Thirty-seven (20.6%) patients had biopsies within 6 months, which decreased from 48.1% as we previously reported. All nine (5%) APW with biopsies triggered only by nEMCs had benign histopathology. The remaining 28 biopsied patients had abnormal bleeding or a thickened endometrium, or they were postmenopausal, including a 53-year-old patient with complex atypical hyperplasia. None of the 138 patients with conservative follow-up developed atypical/malignant lesions.

CONCLUSIONS

A qualifying educational note included in Pap reports significantly reduced follow-up biopsies in APW. Optimal follow-up of nEMCs should be based on relevant clinical modifiers.

Are CIN3 risk or CIN3+ risk measures reliable surrogates for invasive cervical cancer risk?

•Discuss ASCCP guideline. •CIN3 reliable surrogates for cervical cancer? •The Pittsburgh Cervical Cancer Screening Model.

Individualized Bayesian Risk Assessment for Cervical Squamous Neoplasia

Background:

Cervical screening could potentially be improved by better stratifying individual risk for the development of cervical cancer or precancer, possibly even allowing follow-up of individual patients differently than proposed under current guidelines that focus primarily on recent screening test results. We explore the use of a Bayesian decision science model to quantitatively stratify individual risk for the development of cervical squamous neoplasia.

Materials and Methods:

We previously developed a dynamic multivariate Bayesian network model that uses cervical screening and histopathologic data collected over 13 years in our system to quantitatively estimate the risk of individuals for the development of cervical precancer or invasive cervical cancer. The database includes 1,126,048 liquid-based cytology test results belonging to 389,929 women. From-the-vial, high risk human papilloma virus (HPV) test results and follow-up gynecological surgical procedures were available on 33.6% and 12% of these results (378,896 and 134,727), respectively.

Results:

Historical data impacted 5-year cumulative risk for both histopathologic cervical intraepithelial neoplasia 3 (CIN3) and squamous cell carcinoma (SCC) diagnoses. The risk was highest in patients with prior high grade squamous intraepithelial lesion cytology results. Persistent abnormal cervical screening test results, either cytologic or HPV results, were associated with variable increasing risk for squamous neoplasia. Risk also increased with prior histopathologic diagnoses of precancer, including CIN2, CIN3, and adenocarcinoma in situ.

Conclusions:

Bayesian modeling allows for individualized quantitative risk assessments of system patients for histopathologic diagnoses of significant cervical squamous neoplasia, including very rare outcomes such as SCC.

Application of Bayesian network modeling to pathology informatics

BACKGROUND

In the era of extensive data collection, there is a growing need for a large scale data analysis with tools that can handle many variables in one modeling framework. In this article, we present our recent applications of Bayesian network modeling to pathology informatics.

METHODS

Bayesian networks (BNs) are probabilistic graphical models that represent domain knowledge and allow investigators to process this knowledge following sound rules of probability theory. BNs can be built based on expert opinion as well as learned from accumulating data sets. BN modeling is now recognized as a suitable approach for knowledge representation and reasoning under uncertainty. Over the last two decades BN have been successfully applied to many studies on medical prognosis and diagnosis.

RESULTS

Based on data and expert knowledge, we have constructed several BN models to assess patient risk for subsequent specific histopathologic diagnoses and their related prognosis in gynecological cytopathology and breast pathology. These models include the Pittsburgh Cervical Cancer Screening Model assessing risk for histopathologic diagnoses of cervical precancer and cervical cancer, modeling of the significance of benign-appearing endometrial cells in Pap tests, diagnostic modeling to determine whether adenocarcinoma in tissue specimens is of endometrial or endocervical origin, and models to assess risk for recurrence of invasive breast carcinoma and ductal carcinoma in situ.

CONCLUSIONS

Bayesian network models can be used as powerful and flexible risk assessment tools on large clinical datasets and can quantitatively identify variables that are of greatest significance in predicting specific histopathologic diagnoses and their related prognosis. Resulting BN models are able to provide individualized quantitative risk assessments and prognostication for specific abnormal findings commonly reported in gynecological cytopathology and breast pathology.

Enhanced Detection of Cervical Cancer and Precancer Through Use of Imaged Liquid-Based Cytology in Routine Cytology and HPV Cotesting

OBJECTIVES

Cervical screening strives to prevent cervical cancer (CxCa), minimizing morbidity and mortality. Most large US reports on cytology and human papillomavirus (HPV) cotesting of women aged 30 years and older are from one laboratory, which used conventional Papanicolaou (Pap) smears from 2003 to 2009.

METHODS

We quantified detection of CxCa and precancer (cervical intraepithelial neoplasia 3/adenocarcinoma in situ [CIN3/AIS]) in 300,800 cotests at Magee Womens Hospital since 2005. Screening histories preceding CxCa and CIN3/AIS diagnoses were examined to assess the contribution of cytology and HPV testing. Cotesting utilized Food and Drug Administration-approved imaged liquid-based cytology (LBC) and from-the-vial HPV tests.

RESULTS

LBC identified more women subsequently diagnosed with CxCa and CIN3/AIS than HPV testing. HPV-negative/cytology-positive results preceded 13.1% of CxCa and 7.2% of CIN3/AIS diagnoses.

CONCLUSIONS

LBC enhanced cotesting detection of CxCa and CIN3/AIS to a greater extent than previously reported with conventional Pap smear and HPV cotesting.

Primary HPV cervical cancer screening in the United States: Are we ready?

In September 2017, the United States Preventive Services Task Force put forth updated draft guidelines for cervical cancer screening in the United States, which were then open to public comment. The recommendations allowed for every-3-year cervical cytology screening in women aged 21 to 65 years with an option for every-5-year high-risk human papillomavirus testing in women aged 30 to 65 years. There was no option for cotesting. Other recommendations were similar to those published by other professional organizations. The Cytopathology Education and Technology Consortium provided an official response during the open comment period, which is summarized here along with additional commentary by the authors.

Negative Predictive Value and Significance of Benign-Appearing Endometrial Cells in Papanicolaou Tests

OBJECTIVES

Reporting benign-appearing endometrial cells (nEMCs) in Papanicolaou (Pap) smears of women 40 years and older, introduced in The Bethesda System 2001, may be interpreted as an abnormal finding and lead to unnecessary endometrial biopsies. To our knowledge, this is the first study on the negative predictive value (NPV) of this cytology finding.

METHODS

An 11-year database with 1,036,629 Pap test reports and 121,079 surgical pathology reports identified reports of nEMCs in women 40 years and older with follow-up endometrial histopathology within 6 months. Endometrial carcinoma and atypical endometrial hyperplasia were chosen as relevant outcomes. NPVs were calculated. Bayesian modeling assessed the impact of age, bleeding, and postmenopausal status on risk.

RESULTS

NPVs for patients aged 40 to 44 years and 45 to 49 years (99.5% and 99.3%, respectively) were not significantly different. NPVs for patients aged 50 to 54 years, 55 to 59 years, and 60 years and older (97.1%, 95.3%, and 94.5%, respectively) were lower than the NPV for patients aged 40 to 49 years. Bayesian modeling indicated that asymptomatic patients in all age groups 40 years and older have very low risk. Bleeding history increased risk in all age groups, especially in women 50 years and older.

CONCLUSIONS

nEMCs in Pap test reports of women 40 years and older are a normal cytology finding in premenopausal women, which may result in unnecessary endometrial biopsies. The NPV associated with this finding for women aged 40 to 49 years exceeded 99%.

How to interpret the results of medical time series data analysis: Classical statistical approaches versus dynamic Bayesian network modeling

BACKGROUND

Classical statistics is a well-established approach in the analysis of medical data. While the medical community seems to be familiar with the concept of a statistical analysis and its interpretation, the Bayesian approach, argued by many of its proponents to be superior to the classical frequentist approach, is still not well-recognized in the analysis of medical data.

AIM

The goal of this study is to encourage data analysts to use the Bayesian approach, such as modeling with graphical probabilistic networks, as an insightful alternative to classical statistical analysis of medical data.

MATERIALS AND METHODS

This paper offers a comparison of two approaches to analysis of medical time series data: (1) classical statistical approach, such as the Kaplan-Meier estimator and the Cox proportional hazards regression model, and (2) dynamic Bayesian network modeling. Our comparison is based on time series cervical cancer screening data collected at Magee-Womens Hospital, University of Pittsburgh Medical Center over 10 years.

RESULTS

The main outcomes of our comparison are cervical cancer risk assessments produced by the three approaches. However, our analysis discusses also several aspects of the comparison, such as modeling assumptions, model building, dealing with incomplete data, individualized risk assessment, results interpretation, and model validation.

CONCLUSION

Our study shows that the Bayesian approach is (1) much more flexible in terms of modeling effort, and (2) it offers an individualized risk assessment, which is more cumbersome for classical statistical approaches.

Cervical Cancer Screening after Perimenopause: How Is Human Papillomavirus Test Performed?

Cervical cancer is the third most prevalent cancer in women around the world. Recently in Korea, the incidence of cervical cancer has decreased, but in all stages of cervical intraepithelial neoplasia (CIN), CIN has shown a 91% increase from 1999 to 2008. Persistent human papillomavirus (HPV) infection has been found to be the main cause of cervical cancer. HPV types 16 and 18 have been found in 70% of cervical cancer patients around the world. Cervical cancer screening such as cytology has limitations in terms of sensitivity and specificity. A discussion about the need for the HPV test is becoming active in order to compensate for the limitation of cytology. After the role of HPV in cervical cancer was identified, the importance of HPV detection test as a screening was emphasized. Several tests have been developed and each test has its own advantages and disadvantages, and new test method to overcome the disadvantages is still being developed. Today's guidelines and tests are those you would choose from among the large number of cervical cancer screening guidelines and tests, based on the consideration that the selected guidelines and the test are effective.