Abstract
The HPV-Automated Visual Evaluation Consortium is validating a cervical screening strategy enabling accurate cervical screening in resource-limited settings. A rapid, low-cost human papillomavirus (HPV) assay permits sensitive HPV testing of self-collected vaginal specimens; HPV-negative women are reassured. Triage of positive participants combines HPV genotyping (4 groups in order of cancer risk) and visual inspection assisted by automated cervical visual evaluation that classifies cervical appearance as severe, indeterminate, or normal. Together, the combination predicts which women have precancer, permitting targeted management to those most needing treatment. We analyzed CIN3+ yield for each HPV-Automated Visual Evaluation risk level (HPV genotype crossed by automated cervical visual evaluation classification) from 9 clinical sites (Brazil, Cambodia, Dominican Republic, El Salvador, Eswatini, Honduras, Malawi, Nigeria, and Tanzania). Data from 1832 HPV-positive participants confirmed that HPV genotype and automated cervical visual evaluation classification strongly and independently predict risk of histologic CIN3+. The combination of these low-cost tests provided excellent risk stratification, warranting pre-implementation demonstration projects.
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Oxford University Press
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Brian Befano, Jayashree Kalpathy-Cramer, Didem Egemen, Federica Inturrisi, José Jeronimo, Ana Cecilia Rodríguez, Nicole Campos, Miriam Cremer, Ana Ribeiro, Kayode Olusegun Ajenifuja, Andrew Goldstein, Amna Haider, Karen Yeates, Margaret Madeleine, Teresa Norris, Jacqueline Figueroa, Karla Alfaro, Tainá Raiol, Clement Adepiti, Judith Norman, George Kassim Chilinda, Bariki Mchome, Yeycy Donastorg, Xolisile Dlamini, Gabriel Conzuelo, Adekunbiola A Banjo, Pauline Chone, Alex Mremi, Arismendy Benitez, Zeev Rosberger, Te Vantha, Ignacio Prieto-Egido, Jen Boyd-Morin, Christopher Clark, Scott Kinder, Nicolas Wentzensen, Kanan Desai, Rebecca Perkins, Silvia de Sanjosé, Mark Schiffman, PAVE Consortium , Initial evaluation of a new cervical screening strategy combining human papillomavirus genotyping and automated visual evaluation: the Human Papillomavirus–Automated Visual Evaluation Consortium, JNCI: Journal of the National Cancer Institute, Volume 117, Issue 10, October 2025, Pages 2124–2129, https://doi.org/10.1093/jnci/djaf054



