Evidence map›Paper›PMID 29949235›Full record

SynthesisCancer science2018

MicroRNAs as potential biomarkers for the diagnosis of glioma: A systematic review and meta-analysis.

Qian Zhou, Jing Liu, Jing Quan, Wenlan Liu, Hui Tan, Weiping Li

Open access · goldAbstract readMeta-AnalysisSystematic Review
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in Cancer science, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 89 papers, 9 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
89citing papers in PubMed, 9 pooled it
9.9field-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

89 citing papers in PubMed, 9 syntheses or guidelines pooled it, 184 citations in OpenAlex.

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29 more citing papers are in PubMed but not listed here.

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 3 institutions in 1 country.

Qian ZhouDepartment of Neurosurgery and Shenzhen Key Laboratory of Neurosurgery, Shenzhen University 1st Affiliated Hospital, Shenzhen Second People's Hospital, Shenzhen, China.
Jing LiuDepartment of Neurosurgery and Shenzhen Key Laboratory of Neurosurgery, Shenzhen University 1st Affiliated Hospital, Shenzhen Second People's Hospital, Shenzhen, China.
Jing QuanDepartment of Clinical Medicine College, Anhui Medical University, Hefei, China.
Wenlan LiuDepartment of Neurosurgery and Shenzhen Key Laboratory of Neurosurgery, Shenzhen University 1st Affiliated Hospital, Shenzhen Second People's Hospital, Shenzhen, China.
Hui TanDepartment of Neurosurgery and Shenzhen Key Laboratory of Neurosurgery, Shenzhen University 1st Affiliated Hospital, Shenzhen Second People's Hospital, Shenzhen, China.
Weiping LiDepartment of Neurosurgery and Shenzhen Key Laboratory of Neurosurgery, Shenzhen University 1st Affiliated Hospital, Shenzhen Second People's Hospital, Shenzhen, China.ORCID http://orcid.org/0000-0002-4391-3112
Anhui Medical University · CNShenzhen Second People's Hospital · CNSun Yat-sen University · CN

Funding

China Postdoctoral Science Foundation 2017M622881Prevention Public Service Platform improving programReform Commissions Stroke ScreeningThe Health and Family Planning Commission of Guangdong province A2018116The National Natural Science Foundation of China 81772685The Shenzhen Science and Technology Innovation Commission GCZX2015050411225563The Shenzhen Science and Technology Innovation Commission GJHZ20160301163419476The Shenzhen Science and Technology Innovation Commission JCYJ20170306090714854The Shenzhen Science and Technology Innovation Commission JCYJ20170413173149177The Shenzhen Science and Technology Innovation Commission JCYJ 20170817171930009
6 · The paper itself

Abstract

Glioma is the most common central nervous system tumor and associated with poor prognosis. Identifying effective diagnostic biomarkers for glioma is particularly important in order to guide optimizing treatment. MicroRNAs (miRNAs) have drawn much attention because of their diagnostic value in diverse cancers, including glioma. We summarized studies to identify the potential diagnostic values of miRNAs in glioma patients. We included articles reporting miRNAs for differentiation of glioma patients from controls. We calculated sensitivities, specificities, and area under the curves (AUC) of individual miRNA and miRNA panels. We found that overall sensitivity, specificity, and AUC of miRNAs in diagnosis of glioma were 85% (95% confidence interval [CI]: 0.81-0.89), 90% (95% CI 0.85-0.93), and 93% (95% CI 0.91-0.95), respectively. Meta-regression analysis showed that the detection of miRNAs expression in cerebrospinal fluid (CSF) and brain tissue largely improved the diagnostic accuracy. Likewise, panels of multiple miRNAs could enhance the pooled sensitivity. Moreover, AUC of miR-21 was 0.88, with 86% sensitivity and 94% specificity. This study demonstrated that miRNAs could function as potential diagnosis markers in glioma. Detection of miRNAs in CSF and brain tissue displays high accuracy in the diagnosis of glioma.

Indexed as

Biomarkers, TumorBrainBrain NeoplasmsGliomaHumansMicroRNAsSensitivity and SpecificityBiomarkers, TumorMicroRNAsbiomarkerdiagnosisgliomameta-analysismiRNAs

Identifiers

PMID29949235
PMCPMC6125451
OpenAlexW2810223238

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.