Evidence map›Paper›PMID 35280380›Full record

ArticleAnnals of translational medicine2022

New prognostic biomarker

Shoubin Li, Peng Gao, Xingliang Dai, Lei Ye, Zhongyong Wang, Hongwei Cheng

Open access · diamondAbstract read
In one paragraph

Article in Annals of translational medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.2field-weighted citation impact, top 21% 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

10 citing papers in PubMed, 13 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 at 3 institutions in 1 country.

Shoubin LiDepartment of Neurosurgery, the First Affiliated Hospital of Anhui Medical University, Hefei, China.
Peng GaoDepartment of Neurosurgery, the First Affiliated Hospital of Anhui Medical University, Hefei, China.
Xingliang DaiDepartment of Neurosurgery, the First Affiliated Hospital of Anhui Medical University, Hefei, China.
Lei YeDepartment of Neurosurgery, the First Affiliated Hospital of Anhui Medical University, Hefei, China.
Zhongyong WangDepartment of Neurosurgery, the Second Affiliated Hospital of Soochow University, Suzhou, China.
Hongwei ChengDepartment of Neurosurgery, the First Affiliated Hospital of Anhui Medical University, Hefei, China.
First Affiliated Hospital of Anhui Medical University · CNAnhui Medical University · CNSecond Affiliated Hospital of Soochow University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The CKLF-like MARVEL transmembrane domain-containing 3 ( Methods: The tumor data in this study were derived from the sequencing data of various tumors in The Cancer Genome Atlas (TCGA) database. Low-grade glioma (LGG) data in the TCGA database include sequencing and clinical data. Clinical data mainly include survival time, survival outcome, age, WHO classification and other information. Sequencing data for normal tissues were obtained from the Genotype Tissue Expression (GTEx) database. Statistical analyses were mainly performed using bioinformatics tools and the corresponding R software (version 3.6.3). The Mann-Whitney U test (Wilcoxon rank sum test) was used to compare the expression differences between the tumor group and the normal group. Survival analysis was conducted using log-rank test to compare whether the overall survival (OS) time was statistically different between the Results: The results showed that the expression of Conclusions: The

Indexed as

bioinformaticsCKLF-like MARVEL transmembrane domain-containing 3 (CMTM3)gliomaThe Cancer Genome Atlas (TCGA)

Identifiers

PMID35280380
PMCPMC8908177
OpenAlexW4214591844

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.