Evidence map›Paper›PMID 32493989›Full record

ArticleScientific reports2020

Applying Serum Proteins and MicroRNA as Novel Biomarkers for Early-Stage Cervical Cancer Detection.

Shengye Du, Yinghui Zhao, Changyu Lv, Meiling Wei, Zheng Gao, Xianhua Meng

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 3 pooled it
1.6field-weighted citation impact, top 17% 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

25 citing papers in PubMed, 3 syntheses or guidelines pooled it, 44 citations in OpenAlex.

  1. Liquid Biopsy Biomarkers for Cervical Cancer: A Systematic Review.International journal of molecular sciences · 2025
    Pooled it
  2. Pooled it
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  4. MicroRNAs as Biomarkers of Cervical Cancers.International journal of molecular sciences · 2026
    Review
  5. Review
  6. Review
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  8. Review
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  10. Advances in cervical cancer: current insights and future directions.Cancer communications (London, England) · 2025
    Review
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  12. Liquid Biopsy in the Clinical Management of Cancers.International journal of molecular sciences · 2024
    Review
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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

6 authors at 2 institutions in 1 country.

Shengye DuDepartment of Obstetrics and Gynecology, Jinan People's Hospital Affiliated to Shandong First Medical University, No. 001 Xuehu Street at Northern Changshao Road, Laiwu District, Jinan, Shandong, 271199, China.
Yinghui ZhaoDepartment of Obstetrics and Gynecology, Jinan People's Hospital Affiliated to Shandong First Medical University, No. 001 Xuehu Street at Northern Changshao Road, Laiwu District, Jinan, Shandong, 271199, China.
Changyu LvDepartment of Obstetrics and Gynecology, Jinan People's Hospital Affiliated to Shandong First Medical University, No. 001 Xuehu Street at Northern Changshao Road, Laiwu District, Jinan, Shandong, 271199, China.
Meiling WeiDepartment of Obstetrics and Gynecology, Jinan People's Hospital Affiliated to Shandong First Medical University, No. 001 Xuehu Street at Northern Changshao Road, Laiwu District, Jinan, Shandong, 271199, China.
Zheng GaoDepartment of Obstetrics and Gynecology, Jinan People's Hospital Affiliated to Shandong First Medical University, No. 001 Xuehu Street at Northern Changshao Road, Laiwu District, Jinan, Shandong, 271199, China.
Xianhua MengDepartment of Obstetrics and Gynecology, Jinan People's Hospital Affiliated to Shandong First Medical University, No. 001 Xuehu Street at Northern Changshao Road, Laiwu District, Jinan, Shandong, 271199, China. xianhua_meng@163.com.
Jinan City People's Hospital · CNShandong First Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recently, we have been seeing emerging applications of non-invasive approaches using serum biomarkers including miRNA and proteins in detection of multiple cancers. Currently, majority of these methods only use solitary type of biomarkers, which often lead to non-satisfactory sensitivity and specificity in clinical applications. To this end, we established a unique biomarker panel in this study, which determined both squamous cell carcinoma antigen (SCC Ag) degree and miRNA-29a, miRNA-25, miRNA-486-5p levels in blood for detection of early-stage cervical cancer. We designed our study with two phases: a biomarker discovery phase, followed by an independent validation phase. In total of 140 early-stage cervical cancer patients (i.e., AJCC stage I and II) and 140 healthy controls recruited in the biomarker discovery phase, we achieved sensitivity of 88.6% and specificity of 92.9%. To further assess the predictive power of our panel, we used it to an independent patient cohort that consisted of 60 early-stage cervical cancer individuals as well as 60 healthy controls, and successfully achieved both high sensitivity (80.0%) and high specificity (96.7%). Our study indicated combining analyses of multiple serum biomarkers could improve the accuracy of non-invasive detection of early-stage cervical cancer, and potentially serve as a new liquid biopsy approach for detecting early-stage cervical cancer.

Indexed as

AdultAntigens, NeoplasmBiomarkers, TumorBlood ProteinsEarly Detection of CancerFemaleGene Expression ProfilingGenetic TestingHumansLiquid BiopsyMicroRNAsROC CurveSensitivity and SpecificitySerpinsUterine Cervical NeoplasmsAntigens, NeoplasmBiomarkers, TumorBlood ProteinsMicroRNAsMIRN25 microRNA, humanMIRN29a microRNA, humanMIRN486 microRNA, humanSerpinssquamous cell carcinoma-related antigen

Identifiers

PMID32493989
PMCPMC7271168
OpenAlexW3031928792

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.