Evidence map›Paper›PMID 35795701›Full record

ArticleFrontiers in public health2022

Utility of Scoring System for Screening and Early Warning of Cervical Cancer Based on Big Data Analysis.

Dan Hou, Binjie Yang, Yangdan Li, Ming Sun

Open access · goldAbstract read
In one paragraph

Article in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. 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

4 authors at 2 institutions in 1 country.

Dan HouDepartment of Health Medicine, General Hospital of Northern Theater Command, Shenyang, China.
Binjie YangDepartment of Health Medicine, General Hospital of Northern Theater Command, Shenyang, China.
Yangdan LiChina Medical University, Shenyang, China.
Ming SunDepartment of Health Medicine, General Hospital of Northern Theater Command, Shenyang, China.
General Hospital of Shenyang Military Region · CNChina Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To explore the utility of the scoring system for screening and early warning of cervical cancer based on big data analysis. Methods: A total of 420 women undergoing physical examination in Shenyang from January 2021 to January 2022 were screened by convenient sampling as the study subjects. All females accepted the human papilloma virus (HPV) tests and thin-prep cytology test (TCT), a Rating Questionnaire for Screening and Early Warning of Cervical Cancer was developed, and a warning threshold was derived according to the scores of the questionnaire and the goodness of fit for the results of HPV+TCT tests. The patients were graded according to the threshold, and corresponding intervention strategies for patients of different grades were developed. Results: Among the 420 people undergoing physical examination, 92 (21.90%) obtained scores ≥8 points, and 328 (78.10%) obtained scores < 8 points; in diagnosing cervical cancer, the Rating Questionnaire for Screening and Early Warning of Cervical Cancer had an AUC value of 0.848, specificity of 97.22%, and sensitivity of 86.46%; after scientific intervention, HPV test results showed a significant decrease in both high-risk positive cases and low-risk positive cases ( Conclusion: The scoring system for screening and early warning of cervical cancer based on big data analysis presents certain clinical value in the clinical screening of cervical cancer, which can further improve the screening coverage, is of great significance for the diagnosis and treatment of disease, and helps physician implement hierarchical diagnosis and treatment quickly and precisely.

Indexed as

Papillomavirus InfectionsUterine Cervical NeoplasmsData AnalysisEarly Detection of CancerFemaleHumansSensitivity and Specificitybig data analysiscervical cancer screeningintervention measuresscoring system for early warningutility

Identifiers

PMID35795701
PMCPMC9251193
OpenAlexW4283169390

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.