Journal of Pathology Informatics Journal of Pathology Informatics
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ORIGINAL ARTICLE
Year : 2020  |  Volume : 11  |  Issue : 1  |  Page : 9

Individualized bayesian risk assessment for cervical squamous neoplasia


1 Department of Pathology, University of Pittsburgh Medical Center, Magee-Womens Hospital, Pittsburgh, Pennsylvania, USA
2 Department of Pathology, University of Pittsburgh Medical Center, Magee-Womens Hospital, Pittsburgh, Pennsylvania, USA; Faculty of Computer Science, Bialystok University of Technology, Bialystok, Poland

Correspondence Address:
Prof. R Marshall Austin
Department of Pathology, University of Pittsburgh Medical Center, Magee-Womens Hospital, Room No. 4427, 300 Halket Street, Pittsburgh, Pennsylvania 15213
USA
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/jpi.jpi_66_19

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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. 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.


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