Evidence map›Paper›PMID 27438144›Full record

ArticleOncotarget2016

The prognostic value of a seven-microRNA classifier as a novel biomarker for the prediction and detection of recurrence in glioma patients.

Wanghao Chen, Qiang Yu, Bo Chen, Xingyu Lu, Qiaoyu Li

Open access · diamondAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Oncotarget, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 5 pooled it
1.2field-weighted citation impact, top 23% 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

18 citing papers in PubMed, 5 syntheses or guidelines pooled it, 23 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

5 authors at 2 institutions in 1 country.

Wanghao ChenDepartment of Neurosurgery, People's Hospital Affiliated to Jiangsu University, Zhenjiang, Jiangsu Province, China.
Qiang YuDepartment of Neurosurgery, People's Hospital Affiliated to Jiangsu University, Zhenjiang, Jiangsu Province, China.
Bo ChenDepartment of Neurosurgery, People's Hospital Affiliated to Jiangsu University, Zhenjiang, Jiangsu Province, China.
Xingyu LuDepartment of Neurosurgery, People's Hospital Affiliated to Jiangsu University, Zhenjiang, Jiangsu Province, China.
Qiaoyu LiDepartment of Neurosurgery, People's Hospital Affiliated to Jiangsu University, Zhenjiang, Jiangsu Province, China.
Affiliated Hospital of Jiangsu University · CNJiangsu University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Glioma is often diagnosed at a later stage, and the high risk of recurrence remains a major challenge. We hypothesized that the microRNA expression profile may serve as a biomarker for the prognosis and prediction of glioblastoma recurrence. We defined microRNAs that were associated with good and poor prognosis in 300 specimens of glioblastoma from the Cancer Genome Atlas. By analyzing microarray gene expression data and clinical information from three random groups, we identified 7 microRNAs that have prognostic and prognostic accuracy: microRNA-124a, microRNA-129, microRNA-139, microRNA-15b, microRNA-21, microRNA-218 and microRNA-7. The differential expression of these miRNAs was verified using an independent set of glioma samples from the Affiliated People's Hospital of Jiangsu University. We used the log-rank test and the Kaplan-Meier method to estimate correlations between the miRNA signature and disease-free survival/overall survival. Using the LASSO model, we observed a uniform significant difference in disease-free survival and overall survival between patients with high-risk and low-risk miRNA signature scores. Furthermore, the prognostic capability of the seven-miRNA signature was demonstrated by receiver operator characteristic curve analysis. A Circos plot was generated to examine the network of genes and pathways predicted to be targeted by the seven-miRNA signature. The seven-miRNA-based classifier should be useful in the stratification and individualized management of patients with glioma.

Indexed as

AdultAgedArea Under CurveBiomarkers, TumorBrain NeoplasmsDisease-Free SurvivalFemaleGliomaHumansKaplan-Meier EstimateMaleMicroRNAsMiddle AgedNeoplasm Recurrence, LocalPrognosisProportional Hazards ModelsBiomarkers, TumorMicroRNAsgliomaLASSO modelmiRNAprognosisrecurrence

Identifiers

PMID27438144
PMCPMC5288195
OpenAlexW2475197127

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.