Evidence map›Paper›PMID 33634092›Full record

ArticleFrontiers in cell and developmental biology2020

A Novel Signature Constructed by RNA-Binding Protein Coding Genes to Improve Overall Survival Prediction of Glioma Patients.

Zewei Tu, Lei Shu, Jingying Li, Lei Wu, Chuming Tao, Minhua Ye, Xingen Zhu, Kai Huang

Open access · goldAbstract read
In one paragraph

Article in Frontiers in cell and developmental biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
2.4field-weighted citation impact, top 10% 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

14 citing papers in PubMed, 1 synthesis or guideline pooled it, 30 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

8 authors at 3 institutions in 1 country.

Zewei TuDepartment of Neurosurgery, The Second Affiliated Hospital of Nanchang University, Nanchang, China.
Lei ShuDepartment of Neurosurgery, The Second Affiliated Hospital of Nanchang University, Nanchang, China.
Jingying LiDepartment of Comprehensive Intensive Care Unit, The Second Affiliated Hospital of Nanchang University, Nanchang, China.
Lei WuDepartment of Neurosurgery, The Second Affiliated Hospital of Nanchang University, Nanchang, China.
Chuming TaoDepartment of Neurosurgery, The Second Affiliated Hospital of Nanchang University, Nanchang, China.
Minhua YeDepartment of Neurosurgery, The Second Affiliated Hospital of Nanchang University, Nanchang, China.
Xingen ZhuDepartment of Neurosurgery, The Second Affiliated Hospital of Nanchang University, Nanchang, China.
Kai HuangDepartment of Neurosurgery, The Second Affiliated Hospital of Nanchang University, Nanchang, China.
Second Affiliated Hospital of Nanchang University · CNInstitute of Remote Sensing and Digital Earth · CNNanchang University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

RNA binding proteins (RBPs) have been reported to be involved in cancer malignancy but related functions in glioma have been less studied. Herein, we screened 14 prognostic RBP genes and constructed a risk signature to predict the prognosis of glioma patients. Univariate Cox regression was used to identify overall survival (OS)-related RBP genes. Prognostic RBP genes were screened and used to establish the RBP-signature using the least absolute shrinkage and selection operator (Lasso) method in The Cancer Genome Atlas (TCGA) cohort. The 14 RBP genes signature showed robust and stable prognostic value in the TCGA training (

Indexed as

biomarkergliomaoverall survivalprognostic signatureRNA binding protein

Identifiers

PMID33634092
PMCPMC7901892
OpenAlexW3127056801

What OpenQuestion holds

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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.