Evidence map›Paper›PMID 39375610›Full record

ArticleBMC infectious diseases2024

Epidemiological study of human papillomavirus infection in 105,679 women in Wuhan, China.

Weina Guo, Zhao Hu, Jun Yan, Xin Shen, Qingjie Meng, Huan Wu, Yun Xiang, Cong Yao, Keye Du

Abstract read
In one paragraph

Article in BMC infectious diseases, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Weina Guo *Department of Laboratory Medicine, Wuhan Children's Hospital, Wuhan Maternal and Child Healthcare Hospital, Tongji Medical College,Huazhong University of Science & Technology, Wuhan, PR China.
Zhao Hu *Information Department, Wuhan Children's Hospital, Wuhan Maternal and Child Healthcare Hospital, Tongji Medical College,Huazhong University of Science & Technology, Wuhan, PR China.
Jun Yan *Department of Laboratory Medicine, Wuhan Children's Hospital, Wuhan Maternal and Child Healthcare Hospital, Tongji Medical College,Huazhong University of Science & Technology, Wuhan, PR China.
Xin ShenDepartment of Laboratory Medicine, Wuhan Children's Hospital, Wuhan Maternal and Child Healthcare Hospital, Tongji Medical College,Huazhong University of Science & Technology, Wuhan, PR China.
Qingjie MengDepartment of Laboratory Medicine, Wuhan Children's Hospital, Wuhan Maternal and Child Healthcare Hospital, Tongji Medical College,Huazhong University of Science & Technology, Wuhan, PR China.
Huan WuDepartment of Laboratory Medicine, Wuhan Children's Hospital, Wuhan Maternal and Child Healthcare Hospital, Tongji Medical College,Huazhong University of Science & Technology, Wuhan, PR China.
Yun XiangDepartment of Laboratory Medicine, Wuhan Children's Hospital, Wuhan Maternal and Child Healthcare Hospital, Tongji Medical College,Huazhong University of Science & Technology, Wuhan, PR China.
Cong YaoHealth Care, Wuhan Children's Hospital, Wuhan Maternal and Child Healthcare Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, PR China. yaocsmart@163.com.
Keye DuDepartment of Neurosurgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China. keyedu1201@foxmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundQuality assessment of the prevalence and distribution of human papillomavirus (HPV) genotypes could support additional targeted HPV vaccinations. However, the characteristics of HPV infection in Wuhan city are limited in the past decade. We aimed to assess the epidemiology of HPV infection among women and provide a reference for the prevention and treatment of cervical cancer in this region.

methodsA retrospective study employing 105,679 women attending Wuhan Medical and Health Center for Women and Children for cervical cancer screening from January 2015 to December 2022 was conducted. The HPV genotype was detected by polymerase chain reaction (PCR) and diversion hybridization. The overall incidence and age-specific type distribution of HPV infection and the relationship between HPV infection and cervical cytology were analyzed.

resultsThe overall HPV infection rate was 16.87% in Wuhan city, and the prevalence rates of high-risk, low-risk and mixed high- and low-risk HPV infections were 13.64%, 1.77% and 1.46%, respectively. The five most prevalent genotypes were HPV52 (4.24%), HPV58 (2.42%), HPV16 (2.34%), HPV53 (1.87%), and HPV39 (1.66%). The prevalence of HPV in women exhibited a "two-peak" pattern, the peaks of which were observed in the < 21 years group (37.4%) and the 61-65 years group (41.72%). Logistic regression analysis revealed no significant difference in the rate of high-grade lesion positivity between single and multiple high-risk HPV infections. Among patients with a high-grade squamous intraepithelial lesion+ (HSIL+) ThinPrep cytologic test (TCT) diagnosis, HPV58 was the most common type, followed by HPV52, HPV16, HPV39 and HPV53.

conclusionsHPV types 52, 58, 16, 53, and 39 were the most common types in the general female population in Wuhan, and the prevalence of HPV infection varied among different age groups. This study provides a comprehensive overview of the epidemiological characteristics of HPV infection in women, which could support the development of targeted prevention and control strategies for cervical cancer in the region.

Indexed as

GenotypePapillomaviridaePapillomavirus InfectionsAdolescentAdultAgedChinaFemaleHumansIncidenceMiddle AgedPrevalenceRetrospective StudiesUterine Cervical NeoplasmsYoung AdultGenotypesHuman papillomavirusPrevalenceThinPrep cytologic test

Identifiers

PMID39375610
PMCPMC11457396

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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.