Publications by authors named "Agnieszka Onisko"

There is a widespread belief in the Bayesian network (BN) community that while the overall accuracy of the results of BN inference is not sensitive to the precision of parameters, it is sensitive to the structure. We report on the results of a study focusing on the parameters in a companion paper, while this paper focuses on the BN graphical structure. We present the results of several experiments in which we test the impact of errors in the BN structure on its accuracy in the context of medical diagnostic models.

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There is a widely spread belief in the Bayesian network (BN) community that the overall accuracy of results of BN inference is not too sensitive to the precision of their parameters. We present the results of several experiments in which we put this belief to a test in the context of medical diagnostic models. We study the deterioration of accuracy under random symmetric noise but also biased noise that represents overconfidence and underconfidence of human experts.

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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.

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Introduction: Cervical screening has decreased the incidence of cervical carcinoma around the world primarily by preventing cervical squamous carcinoma, with significantly less measurable protective benefits in prevention of cervical adenocarcinoma. In this study, we apply Bayesian modeling of cervical clinical, screening, and biopsy data from a large integrated health system to explore the feasibility of calculating personalized risk assessments on screened system patients for subsequent histopathologic diagnoses of invasive cervical adenocarcinoma (AdCa) or cervical adenocarcinoma in situ (AIS).

Materials And Methods: Diagnoses of cervical AIS or AdCa rendered between 2005 and 2018 were identified in our large health system database with 1,053,713 cytology results, 354,843 high-risk (hr) human papillomavirus (HPV) test results, and 99,012 cervical histopathologic results.

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

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Objectives: Given the recent debate challenging the contribution of cytology in cervical screening, we evaluated results of liquid-based cytology (LBC) and human papillomavirus (HPV) testing in cotesting preceding cervical cancer (CxCa) and precancer diagnoses in a national, heterogeneous population.

Methods: We assessed the results of cotesting, performed by Quest Diagnostics, in 13,633,071 women 30 years and older, tested 2010 to 2018. Cotest results preceding CxCa or precancer diagnoses were analyzed and stratified by histopathology.

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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.

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Uterine carcinosarcomas (UCS) are rare and highly aggressive tumors. Although it is currently accepted that the majority of UCS are metaplastic carcinomas, their aggressive behavior is unparalleled to that of any other high-grade endometrial neoplasms. Therefore, the search for the distinct immunohistochemical and molecular features that could help in the development of new treatment strategies continues.

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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.

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Biomarker analysis of invasive breast carcinoma is useful for prognosis, as surrogate for molecular subtypes of breast cancer, and prediction of response to adjuvant and neoadjuvant systemic therapies. Breast cancer intratumoral heterogeneity is incompletely studied. Comprehensive biomarker analysis of estrogen receptor (ER), progesterone receptor (PR), HER2, and Ki67 labeling index was performed on each tissue block of 100 entirely submitted breast tumors in 99 patients.

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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.

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Aims: Pathologists provide expert tissue assessment of breast cancer, yet their value to guide the appropriate use of breast cancer gene expression profile tests (GEPT) is underutilised. The specific aims of this study are to report morpho-immunohistological characteristics of breast tumours with Oncotype DX (ODx) recurrence scores (RS) of 10 or fewer (ultra-low risk) and 25 or fewer (low risk) in order to determine if pathologists can identify prospectively patient tumours that do not require ODx testing.

Methods And Results: Oncotype DX cases with RS < 10 from 2005 to 2010 comprised 441 of 2594 (17%) of clinical cases; this cohort had 5 years' follow-up and was treated with endocrine therapy alone.

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Biomarker analysis of metastatic breast carcinoma (MBC) is routinely recommended by ASCO/CAP guidelines, and establishing a diagnosis of MBC often requires immunohistochemistry (IHC). The reliability of breast tumor biomarkers and breast-specific markers on decalcified tissues has not been extensively studied. We performed IHC studies on breast tumors exposed to hydrochloric acid (HCl) and formic acid (FA) decalcification solutions, and HER2 fluorescence in situ hybridization on a subset of these tumors to establish a protocol for handling bone specimens with suspicion for MBC.

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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.

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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.

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Introduction: Questions have recently been raised about the acceptability of increased cervical cancer risk projected with the new guideline-recommended rescreening interval of 5 years after negative cytology and human papillomavirus (HPV) cotest results. Additional data sources capable of evaluating cervical cancer risk over time are being sought. We employed the continuously updated Bayesian Pittsburgh Cervical Cancer Screening Model (PCCSM) to estimate invasive cancer risks for patients screened at extended screening intervals after negative HPV test results.

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Objective: One of the hardest technical tasks in employing Bayesian network models in practice is obtaining their numerical parameters. In the light of this difficulty, a pressing question, one that has immediate implications on the knowledge engineering effort, is whether precision of these parameters is important. In this paper, we address experimentally the question whether medical diagnostic systems based on Bayesian networks are sensitive to precision of their parameters.

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Objectives: It is clinically important to determine whether adenocarcinoma present in a biopsy or curettage is of endometrial or endocervical origin. When tumors are difficult to distinguish based on routine histologic sections, immunohistochemistry and human papillomavirus (HPV) in situ hybridization may be used.

Materials And Methods: We compare immunohistochemical profile and HPV expression in 76 tumors, including various types of endocervical adenocarcinoma and the most common endometrioid type of endometrial adenocarcinoma using tumor tissue microarray.

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The assessment of hormone receptors, including estrogen receptor and progesterone receptor, has become a standard practice in breast cancer management. However, the need for multiple sections to evaluate each receptor individually by conventional immunohistochemistry may preclude the analysis on some core biopsies with a limited amount of tumors. The aim of the study was to validate the quantitative analysis of nuclear markers estrogen receptor and progesterone receptor by quantum dot-based immunohistochemistry using a multispectral imaging system in ductal carcinoma in situ of the breast.

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Objective: This study aimed to follow a large group of US women with negative computer-imaged liquid-based cytology (LBC) and positive high risk (hr) HPV DNA results.

Methods: Negative LBC and positive hrHPV cases were identified between July 1, 2005 and December 31, 2009. Cytologic and histopathologic follow-up results, repeat HPV results, and prior history were analyzed.

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Context: Evaluation of cervical cancer screening has grown increasingly complex with the introduction of human papillomavirus (HPV) vaccination and newer screening technologies approved by the US Food and Drug Administration.

Objective: To create a unique Pittsburgh Cervical Cancer Screening Model (PCCSM) that quantifies risk for histopathologic cervical precancer (cervical intraepithelial neoplasia [CIN] 2, CIN3, and adenocarcinoma in situ) and cervical cancer in an environment predominantly using newer screening technologies.

Design: The PCCSM is a dynamic Bayesian network consisting of 19 variables available in the laboratory information system, including patient history data (most recent HPV vaccination data), Papanicolaou test results, high-risk HPV results, procedure data, and histopathologic results.

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Objective: Atypical glandular cell (AGC) Pap interpretations and screening for glandular neoplasias remain major challenges. We document the largest reported AGC histopathologic follow-up experience and include verification bias-adjusted data on laboratory screening sensitivity.

Methods: AGC Pap tests of endocervical origin (AGC-EC), endometrial origin (AGC-EM), and not otherwise specified (AGC-NOS) were documented at a center serving an older low risk population.

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There is dearth of studies that provide a practical working formulation of breast cancer gene expression analysis for the surgical pathologist. ER, PR, HER2 were used as surrogate markers to classify 205 breast carcinomas into molecular classes. Ki-67 labeling index was calculated using an image analysis system.

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Objective: Study the decision to issue a boil-water advisory in response to a spike in sales of diarrhea remedies or wait 72 hours for the results of definitive testing of water and people.

Methods: Decision analysis.

Results: In the base-case analysis, the optimal decision is test-and-wait.

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