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. Using our continuously updated Bayesian cervical cancer screening model which includes clinical data, cervical screening results, and cervical biopsy results, we projected quantitative estimates of patients’ 5-year cumulative risk for cervical AIS or AdCa. Results: 161 patients were identified with AIS (ages 17–75, mean 37 years), and 99 patients had diagnoses of cervical AdCa (ages 26–91, mean 48 years). Quantitative Bayesian 5-year cumulative risk projections for diagnoses of cervical AdCa or AIS in patients with different cervical screening test and biopsy histories were determined. The highest patient risk projections for subsequent cervical AdCa and/or AIS histopathologic diagnoses were associated with prior cervical screening test results of HPV-positive atypical glandular cells. Prior squamous cytologic abnormalities were associated with lower risk estimates. Prior histopathologic diagnoses of squamous abnormalities also influenced quantitative risk. A prior histopathologic diagnosis of AIS was associated with a very low risk of subsequent AdCa, consistent with effective excisional treatment. AdCa risk was greatest in women aged 30–65 years with prior CIN3 biopsy results, whereas AIS risk was greatest in women <30. Conclusion: Prevention of cervical AdCa in screened patients remains a major challenge for cervical screening. Individualized risk projections for cervical glandular neoplasia reflecting patient age, prior cervical screening test results, and prior cervical biopsy history are feasible using Bayesian modeling of health system data.

Keywords:
Cervical cancer, Cervical adenocarcinoma, Cervical adenocarcinoma in situ, Quantitative risk assessments, Personalized medicine, Bayesian network modeling
© 2020 S. Karger AG, Basel
2020
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