Evidence map›Paper›PMID 31286939›Full record

ArticleBMC women's health2019

HPV genotype prevalence and distribution during 2009-2018 in Xinjiang, China: baseline surveys prior to mass HPV vaccination.

Jing Wang, Dandan Tang, Kai Wang, Jialu Wang, Zhaoxia Zhang, Yanxia Chen, Xueliang Zhang, Cailing Ma

Open access · goldAbstract read
In one paragraph

Article in BMC women's health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers.

0numbers the graph read from it
0cells of the map it votes in
51citing papers in PubMed
9.7field-weighted citation impact, top 1% of its field
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

51 citing papers in PubMed, 99 citations in OpenAlex.

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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

8 authors at 1 institution in 1 country.

Jing WangState Key Laboratory of PPTHIDCA(Pathogenesis, Prevention and Treatment of High Incidence Diseases in Central Asia) / Department of Gynecology, First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang, China.
Dandan TangCollege of Public Health, Xinjiang Medical University, Urumqi, China.
Kai WangDepartment for College of Medical Engineering and Technology, Xinjiang Medical University, Urumqi, Xinjiang, China.
Jialu WangDepartment of Medical laboratory, First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang, China.
Zhaoxia ZhangDepartment of Medical laboratory, First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang, China.
Yanxia ChenState Key Laboratory of PPTHIDCA(Pathogenesis, Prevention and Treatment of High Incidence Diseases in Central Asia) / Department of Gynecology, First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang, China.
Xueliang ZhangDepartment for College of Medical Engineering and Technology, Xinjiang Medical University, Urumqi, Xinjiang, China.
Cailing MaState Key Laboratory of PPTHIDCA(Pathogenesis, Prevention and Treatment of High Incidence Diseases in Central Asia) / Department of Gynecology, First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang, China. hymcl13009661999@126.com.ORCID 0000-0001-9049-5833
Xinjiang Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe aim of this paper was to conduct a baseline survey of HPV infection in unvaccinated women in Xinjiang Uyghur Autonomous Region before the mass use of HPV vaccine.

methodsBetween 2008 and 2018, the HPV genotype detected by a PCR-based hybridization gene chip assay of 37,722 women who were from Gynecology Department and Health Management Center of the First Affiliated Hospital of Xinjiang Medical University were tested HPV genotype by a PCR-based hybridization gene chip assay. All statistical analysis methods were performed with this statistical software including Python version 3.6.1, R Software 3.5.1 and Excel 2011.

resultsThe total positive rate for HPV was 14.02%, the most prevalent genotypes were HPV 16 (3.79%), HPV 52 (2.47%), HPV 58 (1.76%), HPV 53 (1.35%) and HPV 31 (0.72%). The single infection (11.34%) and high-risk HPV (HR-HPV) infection (9.72%) was the main prevalence of HPV. Age-specific HPV distribution was presented as a bimodal curve, while the youngest age group (≤25 years) presented the highest HPV infection rate (20.78%), which was followed by a second peak for the 36-40 age group. According to the ethnic stratification, the HPV infection prevalence ranging from the high to low was: Mongol (16.36%), Hui (15.15%), Kazak (14.47%), Han (14.43%), Other (14.37%), Uygher (10.96%). From 2009 to 2013, the HPV infection rate fluctuated but did not changed much. It peaked in 2014 and then fell significantly, reached the bottom point in 2017 and rose slightly in 2018. In 2015, the infection rate of HPVl6 and 52 in the population was almost the same (both 3.40%) the infection rate of HPV52 type (3.31%) was higher than that of HPVl6 type (2.18%) and became the dominant type in 2016.

conclusionsWe present data regarding the prevalence and type distribution of HPV infection, which could serve as the valuable reference to guide nationwide cervical cancer screening. These baseline data enable the estimates of maximum HPV vaccine impact across time and provide critical reference measurements which are important to the assess of clinical benefits and potential harms in HPV vaccination and the increase in non-vaccine HPV types.

Indexed as

AdultAgedAge DistributionChinaEarly Detection of CancerFemaleGenotypeHumansMass VaccinationMiddle AgedPapillomaviridaePapillomavirus InfectionsPapillomavirus VaccinesPolymerase Chain ReactionPrevalenceSurveys and QuestionnairesPapillomavirus VaccinesGenotype distributionHPV vaccinationHuman papillomaviruXinjiang region

Identifiers

PMID31286939
PMCPMC6615222
OpenAlexW2958936745

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.