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

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.

Reporting of Benign Endometrial Cells in Papanicolaou Tests

OBJECTIVES

The 2014 Bethesda System (TBS 2014) guidelines for reporting cervical cytology revised the age for reporting benign endometrial cells (BECs) from 40 years or older to age 45 years or older. We evaluated this change and further investigated if extending the reporting age to 50 years or older may be acceptable.

METHODS

We reviewed cases with BECs reported on Papanicolaou tests in women age 40 years or older and 45 years or older before and after implementation of TBS 2014. Follow-up endometrial biopsy/curettage results were categorized as benign, endometrial hyperplasia with or without atypia, or malignant. Hyperplasia and malignant follow-up were considered clinically significant. Clinical data were documented. Results were compared for women age 40 to 44, 45 to 49, and 50 years or older.

RESULTS

Follow-up in 15 (100%) women age 40 to 44 years was benign. In women age 45 to 49 years, 61 (96.8%) had benign follow-up, one (1.6%) had atypical hyperplasia, and one (1.6%) had malignant follow-up. In women age 50 years or older, 57 (86.5%) had benign follow-up, four (6%) had malignant follow-up, and seven (7.5%) had atypical or nonatypical hyperplasia. There was a significant difference in follow-up between the age groups of 40 to 49 and 50 or older (P = .023).

CONCLUSIONS

We conclude that the TBS 2014 revision was justified. Our data suggest that age 50 years or older rather than age 45 years or older may be an acceptable cutoff for reporting BECs.

Age cutoff for reporting of benign-appearing endometrial cells in Papanicolaou specimens; should it be raised? A 10-year retrospective study from a large county hospital

INTRODUCTION

The recommendation for reporting benign-appearing endometrial cells in Papanicolaou specimens was increased from 40 to 45 years in the 2014 edition of The Bethesda System. Recent studies suggest that increasing the reporting age to 50 years would have no significant negative impact. Reporting of benign endometrial cells may trigger unnecessary procedures and increase the cost of patient care. The goal of our study was to perform cytohistologic correlations and determine an optimal age cutoff for reporting endometrial cells in cervical cytology specimens.

MATERIALS AND METHODS

The pathology database was searched between 2006 and 2015 for Papanicolaou tests with benign-appearing endometrial cells that were followed by endometrial sampling within 1 year of the cytology result in women ≥45 years. In cases where more than one follow-up surgical specimen was available, only the most significant result was included. Endometrial carcinoma or atypical hyperplasia was considered a significant histologic result. The data were organized into 4 age groups, 45 to 49, 50 to 54, 55 to 59, and ≥60 years.

RESULTS

Among 453,420 Papanicolaou specimens, 1121 cases reported endometrial cells in women ≥45 years. Of these, 588 (52%) had an endometrial biopsy/curettage or hysterectomy. Benign diagnosis was reported for 558 (95%) and 12 (2%) samples were insufficient for diagnosis. Significant histologic findings were present in 18 (3%) of cases, of which all were endometrial carcinoma. The difference was statistically significant between the age groups 45 to 54 and ≥55 (1.5% versus 17% of cases had significant endometrial pathology, P < 0.05).

CONCLUSIONS

Increasing the current reporting age appears safe and may improve efficiency and cost savings.

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.