Evidence map›Paper›PMID 31950024›Full record

ArticleJournal of cancer prevention2019

Usefulness Analysis of Urine Samples for Early Screening of Human Papilloma Virus Infection.

Yoon Sung Choi, Hyunwoo Jin, Kyung Eun Lee

Open access · diamondAbstract read
In one paragraph

Article in Journal of cancer prevention, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.2field-weighted citation impact, top 42% 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

4 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Review
  3. A review of urinary HPV testing for cervical cancer management and HPV vaccine surveillance: rationale, strategies, and limitations.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2024
    Review
  4. Article
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

3 authors at 2 institutions in 1 country.

Yoon Sung ChoiDepartment of Thoracic and Cardiovascular Surgery, Inje University Haeundae Paik Hospital, Busan, Korea.ORCID https://orcid.org/0000-0003-1338-4579
Hyunwoo JinDepartment of Clinical Laboratory Science, College of Health Sciences, Catholic University of Pusan, Busan, Korea.ORCID https://orcid.org/0000-0003-1773-023X
Kyung Eun LeeDepartment of Clinical Laboratory Science, College of Health Sciences, Catholic University of Pusan, Busan, Korea.ORCID https://orcid.org/0000-0001-9543-4159
Catholic University of Pusan · KRInje University Haeundae Paik Hospital · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Human papilloma virus (HPV) is known to be a major cause of cervical cancer. In Korea, although the mortality of cervical cancer has decreased, HPV infection rates are increasing rapidly in young women. One of the reasons for a high rate of human immunodeficiency virus (HIV) infection appears to be associated with a low frequency to visit gynecology clinics because of the uncomfortable sampling process for HPV testing. Therefore, it is necessary to develop a non-invasive method, such as urine testing to diagnose cervical cancer rather than use of the existing invasive method. This study aimed to test validity of HPV DNA detection in urine specimens that can be easily collected from women. Paired vaginal discharge and urine samples were collected prospectively from 203 women who visited the local hospital between January and August 2018 in Busan, Korea. By using the Virocheck

Indexed as

Human papilloma virusUrineVaginal discharge

Identifiers

PMID31950024
PMCPMC6951315
OpenAlexW2998734529

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.