Evidence map›Paper›PMID 32065786›Full record

ArticleCancer biomarkers : section A of Disease markers2020

Low serum exosomal miR-484 expression predicts unfavorable prognosis in ovarian cancer.

Weijia Zhang, Xiaoyan Su, Shuang Li, Zhen Liu, Qian Wang, Hai Zeng

Abstract read
In one paragraph

Article in Cancer biomarkers : section A of Disease markers, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 2 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, 2 syntheses or guidelines pooled it, 34 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

6 authors.

Weijia Zhang
Xiaoyan Su
Shuang Li
Zhen Liu
Qian Wang
Hai Zeng

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOvarian cancer (OC) is one of the most common malignancy worldwide. Emerging evidences have demonstrated that microRNAs (miRNAs) play an important role in regulating the initiation and development of OC.

objectiveThe present study was to explore the clinical significance of serum exosomal miR-484 in OC.

methodsA total of 113 OC patients and 60 healthy volunteers were enrolled in this study. Quantitative real-time polymerase chain reaction (qRT-PCR) was performed to measure serum exosomal miR-484 levels in blood samples.

resultsOur results showed that serum exosomal miR-484 levels were significantly lower in OC patients. Serum exosomal miR-484 was able to discriminate OC cases from controls, with an area under the receiver-operating characteristics (ROC) curve (AUC) of 0.821. Combination of serum exosomal miR-484 with CA-125 showed an elevated AUC of 0.912 in identifying OC patients from controls. Moreover, decreased serum exosomal miR-484 expression was significantly associated with aggressive clinical variables as well as shorter overall survival and progression-free survival. The OC patients with simultaneously low serum exosomal miR-484 expression and high serum CA-125 levels tended to suffer the worst clinical outcomes. The multivariate analysis confirmed that low serum exosomal miR-484 level was an independent indicator.

conclusionsCollectively, serum exosomal miR-484 could serve as a reliable and non-invasive marker for predicting the prognosis of OC.

Indexed as

Biomarkers, TumorCA-125 AntigenCase-Control StudiesExosomesFemaleHumansMembrane ProteinsMicroRNAsMiddle AgedNeoplasm StagingOvarian NeoplasmsPrognosisROC CurveSurvival RateBiomarkers, TumorCA-125 AntigenMembrane ProteinsMicroRNAsMIRN484 microRNA, humanMUC16 protein, humanbiomarkermiR-484Ovarian cancerprognosisserum exosomes

Identifiers

PMID32065786
PMCPMC12662311
OpenAlexW3005620306

What OpenQuestion holds

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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.