Evidence map›Paper›PMID 32660490›Full record

ArticleVirology journal2020

Prevalence of human papillomavirus genotypes and precancerous cervical lesions in a screening population in Beijing, China: analysis of results from China's top 3 hospital, 2009-2019.

Yidi Liu, Qing Ang, Huan Wu, Jingjiang Xu, Defu Chen, Hongyou Zhao, Haolin Liu, Xianghuan Guo, Ying Gu, Haixia Qiu

Abstract read
In one paragraph

Article in Virology journal, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 3 pooled it
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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

17 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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  3. Association BetweenFrontiers in genetics · 2022
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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

10 authors.

Yidi LiuDepartment of Laser Medicine, the First Medical Center, Chinese PLA General Hospital, Beijing, 100853, China.
Qing AngMedical Supplies Center, Chinese PLA General Hospital, Beijing, 100853, China.
Huan WuMedical Big Data Center, Chinese PLA General Hospital, Beijing, 100853, China.
Jingjiang XuSchool of Physics and Optoelectronic Engineering, Foshan University, Foshan, 528000, China.
Defu ChenInstitute of Engineering Medicine, Beijing Institute of Technology, Beijing, 100081, China.
Hongyou ZhaoInstitute of Engineering Medicine, Beijing Institute of Technology, Beijing, 100081, China.
Haolin LiuDepartment of Laser Medicine, the First Medical Center, Chinese PLA General Hospital, Beijing, 100853, China.
Xianghuan GuoDepartment of Laser Medicine, the First Medical Center, Chinese PLA General Hospital, Beijing, 100853, China.
Ying GuDepartment of Laser Medicine, the First Medical Center, Chinese PLA General Hospital, Beijing, 100853, China. guyinglaser301@163.com.ORCID 0000-0002-1729-2092
Haixia QiuDepartment of Laser Medicine, the First Medical Center, Chinese PLA General Hospital, Beijing, 100853, China. qiuhxref@126.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCervical cancer is the fourth most common cancer in women. Early detection and diagnosis play an important role in secondary prevention of cervical cancer. This study aims to provide more information to develop an effective strategy for the prevention and control of cervical cancer in northern China.

methodsA retrospective single-centre descriptive cross-sectional study was conducted in Chinese PLA General Hospital located in Beijing, covering the period from January 2009 to June 2019. The patients who underwent a polymerase chain reaction (PCR)-based HPV genotyping test and cervical pathological diagnosis were included. Furthermore, we limited the interval between the two examination within 180 days for the purpose of making sure their correlation to analyse their relationship. Moreover, the relationship between different cervical lesions and age as well as single/multiple HPV infection was assessed.

resultsA total of 3134 patients were eligible in this study after HPV genotyping test and pathological diagnosis. Most of the patients (95%) were from northern China. Among the patients, 1745(55.68%) had high-grade squamous intraepithelial neoplasia (HSIL), 1354 (43.20%) had low-grade squamous intraepithelial neoplasia (LSIL) and 35 (1.12%) were Normal. The mean age was 42.06 ± 10.82(range, 17-79 years). The women aged 35-49 years accounted for the highest incidence rate. The top five most commonly identified HPV genotypes in each lesion class were as follows: HPV16, 58, 52, 31 and 51 in the class of HSIL; HPV16, 52, 58, 56 and 51 in the class of LSIL; HPV16, 31, 6,11, 52 and 58 in the class of normal. The frequencies of HPV single genotype infection and multiple genotypes infection were 55.26 and 34.18%, respectively. There was no difference in the attributable proportions of multiple genotypes infection amongst HSIL, LSIL and Normal.

conclusionsIn Northern China, HPV16 was the most dominant genotype in the patients with pathological examination. The peak age of the onset of HSIL was between 35 and 49 years of age. Infection with multiple HPV genotypes did not increase the risk of HSIL. Type-specific HPV prevalence and attribution proportion to cervical precancerous lesions should be taken into consideration in the development of vaccines and strategy for screening in this population.

Indexed as

Precancerous ConditionsAdolescentAdultAgedBeijingCervix UteriCross-Sectional StudiesDNA, ViralEarly Detection of CancerFemaleGenotypeHospitalsHumansMass ScreeningMiddle AgedPapillomaviridaeDNA, ViralCervical intraepithelial Neoplasia (CIN)High-grade squamous intraepithelial lesion (HSIL)Human papilloma virus (HPV)Low-grade squamous intraepithelial lesion (LSIL)

Identifiers

PMID32660490
PMCPMC7359485

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Registered trials

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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.