Evidence map›Paper›PMID 42110258›Full record

ArticleFrontiers in public health2026

Nationwide epidemiology of HPV E6/E7 mRNA in China: genotype distribution in 11,118 women.

Shengyang Xu, Yan Li, Xunfei Yi, Zhanli Yan, Tiantian Zeng, Ning Meng, Jingna Sun

Abstract read
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Article in Frontiers in public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Shengyang Xu *Dian Diagnostics Group Co., Ltd., Hangzhou, China.
Yan Li *Department of Gynecology, Tianjin First Central Hospital, Tianjin, China.
Xunfei YiGuangzhou Biotron Biotechnology Co., Ltd., Guangzhou, China.
Zhanli YanDian Diagnostics Group Co., Ltd., Hangzhou, China.
Tiantian ZengDian Diagnostics Group Co., Ltd., Hangzhou, China.
Ning MengGuangzhou Biotron Biotechnology Co., Ltd., Guangzhou, China.
Jingna SunHebei Innovation Center of Clinical Medical Laboratory Technology, Department of Clinical Laboratory, The First Hospital of Hebei Medical University, Shijiazhuang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Persistent infection with carcinogenic human papillomavirus (HPV) is the necessary cause of cervical cancer. However, the distribution of transcriptionally active high-risk HPV genotypes across age groups and geographic regions in China remains insufficiently characterized. We aimed to define the nationwide epidemiologic profile of HPV E6/E7 mRNA positivity in China and to evaluate age-, region-, and proxy-defined source-population heterogeneity. Methods: In this retrospective cross-sectional study, 11,118 female cervical specimens retrieved for HPV E6/E7 mRNA testing between August 14, 2024 and October 23, 2025 were analyzed from seven geographic regions of China. Fourteen high-risk HPV genotypes were detected using the Biotron HPV E6/E7 mRNA Genotyping Assay. Descriptive, co-detection, and multivariable logistic regression analyses with institution-level cluster-robust standard errors were performed. Results: Overall high-risk HPV E6/E7 mRNA positivity was 16.32% (1,815/11,118). HPV52, HPV58, and HPV16 were the dominant genotypes, followed by HPV18 and HPV51. Overall positivity varied significantly across age groups, regions, institution-level proxy categories, and department-based clinical-context proxy categories. Central China had the highest overall positivity rate, whereas East China had the lowest. Significant age-related heterogeneity was observed for several major genotypes, especially HPV52, HPV58, and HPV16. Multi-type positivity accounted for 11.8% of positive samples, with HPV52 and HPV58 forming the most prominent co-detection pattern. In multivariable analyses, older age and several non-East regions were associated with higher odds of overall positivity, whereas the opportunistic screening proxy group showed markedly lower odds of positivity than the gynecology-related clinical attendance proxy group. Conclusion: Transcriptionally active high-risk HPV infection in China is characterized by dominance of HPV52, HPV58, and HPV16 and by marked heterogeneity across age, geography, and proxy-defined testing contexts. These findings may support more refined HPV surveillance and risk-adapted prevention strategies.

Indexed as

Human Papillomavirus VirusesOncogene Proteins, ViralPapillomaviridaePapillomavirus E7 ProteinsPapillomavirus InfectionsRNA, MessengerAdolescentAdultChinaCross-Sectional StudiesFemaleGenotypeHumansMiddle AgedRetrospective StudiesRNA, ViralOncogene Proteins, ViralPapillomavirus E7 ProteinsRNA, MessengerRNA, Viralcervical cancerChinaepidemiologygenotype distributionHPV E6/E7 mRNAhuman papillomavirus

Identifiers

PMID42110258
PMCPMC13153018

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.