Publications by authors named "D Egemen"
Objective: The Enduring Consensus Cervical Cancer Screening and Management Guidelines Committee developed recommendations for the use of extended genotyping results in cervical cancer prevention programs.
Methods: Risks of cervical intraepithelial neoplasia grade 3 or worse were calculated using data obtained with the Onclarity HPV Assay from large cohorts. Management recommendations were based on clinical action thresholds developed for the 2019 American Society for Colposcopy and Cervical Pathology Risk-Based Management Consensus Guidelines.
Article Synopsis
- HPV genotype plays a crucial role in predicting cervical cancer risk, and using genotyping can improve management strategies for HPV-positive patients during cervical screening.
- The ScreenFire HPV RS assay, combined with the Zebra BioDome technology, facilitates efficient testing by processing up to 96 samples in about an hour while minimizing contamination risks with fewer pipetting steps.
- Validation studies on the Zebra BioDome showed excellent repeatability and accuracy when compared to the standard assay, suggesting it could streamline HPV testing and improve accessibility for point-of-care diagnostics in low-resource settings.
Associations of Obesity with Post-Treatment Risks of Cervical Precancer and Cancer.
Am J Obstet Gynecol
December 2024
Background: Individuals with obesity have an increased risk of cervical cancer, in part related to challenges associated with cervical sampling and visualization that result in missed detection of cervical precancers. The influence of obesity on the effectiveness of excisional treatment of detected cervical precancers and post-treatment disease risk is unknown.
Objectives: The aim of this study was to evaluate post-treatment risks of cervical precancer and cancer by body mass index (BMI).
A number of challenges hinder artificial intelligence (AI) models from effective clinical translation. Foremost among these challenges is the lack of generalizability, which is defined as the ability of a model to perform well on datasets that have different characteristics from the training data. We recently investigated the development of an AI pipeline on digital images of the cervix, utilizing a multi-heterogeneous dataset of 9,462 women (17,013 images) and a multi-stage model selection and optimization approach, to generate a diagnostic classifier able to classify images of the cervix into "normal", "indeterminate" and "precancer/cancer" (denoted as "precancer+") categories.
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- Implementation of primary HPV testing in the U.S. is slow, largely due to concerns about its sensitivity compared to cotesting methods, which combine HPV and cytology testing.
- A study of various populations showed that cotesting led to more laboratory tests and colposcopies than primary HPV testing, indicating a higher burden on healthcare resources.
- As the prevalence of cervical issues decreased, the detection of significant conditions through cotesting became less advantageous, suggesting that primary HPV testing may provide a better balance between benefits and risks than cotesting.