{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,7]],"date-time":"2026-10-07T14:01:00Z","timestamp":1791381660574,"version":"4.3.3"},"reference-count":41,"publisher":"Wiley","issue":"5","license":[{"start":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T00:00:00Z","timestamp":1777334400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T00:00:00Z","timestamp":1777334400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100004826","name":"Natural Science Foundation of Beijing Municipality","doi-asserted-by":"publisher","award":["7252123"],"award-info":[{"award-number":["7252123"]}],"id":[{"id":"10.13039\/501100004826","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012151","name":"Sanming Project of Medicine in Shenzhen","doi-asserted-by":"publisher","award":["SZSM202211032"],"award-info":[{"award-number":["SZSM202211032"]}],"id":[{"id":"10.13039\/501100012151","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Journal of Medical Virology"],"published-print":{"date-parts":[[2026,5]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:label\/>\n                    <jats:p>\n                      The aim of this study is to develop a machine learning triage model for HR\u2010HPV positive women based on methylation patterns of human and HPV genes to predict the risk of CIN2\u2009+, and to compare its performance with traditional detection techniques. A total of 512 eligible women participated in the study, with exfoliated cervical cell specimens collected for methylation analysis of both human and HPV genes. Highly methylated gene fragments related to cervical cancer were identified through high density, high association, high MHL (Methylation Haplotype Load) screening and Logistic regression. The samples were divided into a training set and a validation set at a ratio of 7:3, and a machine learning triage model was constructed using CIN2+ as the outcome. Among 512 HR\u2010HPV positive women, 174 (34.0%) had CIN2\u2009+. To construct the random forest model, 10 high methylation human gene fragments were identified from a pool of 45 genes, along with HPV 16, 18, and 52 L2 genes. In the validation set, the random forest model identified 45 samples as positive (38 were true positives) and 112 samples as negative (96 were true negatives). The model achieved an AUC of 0.9, and DeLong test confirmed its performance was significantly superior (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.001) to HPV 16\/18 genotyping and cytology testing. The random forest model constructed based on methylation patterns of human and HPV genes demonstrated strong predictive efficacy for CIN2+ in HR\u2010HPV positive women, and may optimize the triage method in cervical cancer screening.\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/jmv.70930","type":"journal-article","created":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T10:51:12Z","timestamp":1777373472000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Triage Model for HR\u2010HPV Positive Women Based on Methylation of Human and HPV Genes"],"prefix":"10.1002","volume":"98","author":[{"given":"Yuan","family":"Yang","sequence":"first","affiliation":[{"name":"Department of Epidemiology, National Cancer Center\/National Clinical Research Center for Cancer\/Cancer Hospital Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China"},{"name":"Meishan Center for Disease Control and Prevention Meishan China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hang","family":"Zhou","sequence":"additional","affiliation":[{"name":"Department of Epidemiology, National Cancer Center\/National Clinical Research Center for Cancer\/Cancer Hospital Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yakun","family":"Wang","sequence":"additional","affiliation":[{"name":"Healthcare Associated Infection Management Department, Beijing Hospital of Traditional Chinese Medicine Capital Medical University Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hua","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Epidemiology, National Cancer Center\/National Clinical Research Center for Cancer\/Cancer Hospital Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China"},{"name":"The State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Institute of Diagnostics and Vaccine Development in Infectious Diseases, School of Public Health Xiamen University Xiamen China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ruoji","family":"Pi","sequence":"additional","affiliation":[{"name":"Department of Epidemiology, National Cancer Center\/National Clinical Research Center for Cancer\/Cancer Hospital Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China"},{"name":"Medical Department Peking University Third Hospital Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yiran","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Cancer and Pharmaceutical Sciences Faculty of Life Sciences and Medicine Room 2.34A, New Hunt House Guy's Campus, King's College London London England"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yu","family":"Dai","sequence":"additional","affiliation":[{"name":"Department of Epidemiology, National Cancer Center\/National Clinical Research Center for Cancer\/Cancer Hospital Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tingyuan","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Epidemiology, National Cancer Center\/National Clinical Research Center for Cancer\/Cancer Hospital Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China"},{"name":"Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital and Institute, Sichuan Cancer Center Affiliated Cancer Hospital of University of Electronic Science and Technology of China Chengdu China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ziyue","family":"Huang","sequence":"additional","affiliation":[{"name":"Mianyang Maternal and Child Health Care Hospital Mianyang China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jingchang","family":"Du","sequence":"additional","affiliation":[{"name":"School of Public Health Chengdu Medical College Chengdu China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lu","family":"Han","sequence":"additional","affiliation":[{"name":"MyGenostics Inc. 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