Evidence map›Paper›PMID 31396442›Full record

ArticlePeerJ2019

A 3-mRNA-based prognostic signature of survival in oral squamous cell carcinoma.

Ruoyan Cao, Qiqi Wu, Qiulan Li, Mianfeng Yao, Hongbo Zhou

Open access · goldAbstract read
In one paragraph

Article in PeerJ, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
3.7field-weighted citation impact, top 5% 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

22 citing papers in PubMed, 58 citations in OpenAlex.

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  14. Clinical effect of robot-assisted radical cystectomy in bladder cancer.American journal of translational research · 2021
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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 1 institution in 1 country.

Ruoyan CaoDepartment of Prosthodontics, Xiangya Stomatological Hospital & School of Stomatology, Central South University, Changsha, China.
Qiqi WuDepartment of Endodontics, Xiangya Stomatological Hospital & School of Stomatology, Central South University, Changsha, China.
Qiulan LiDepartment of Stomatology, The Second Xiangya Hospital, Central South University, Changsha, China.
Mianfeng YaoDepartment of Stomatology, Xiangya Hospital, Central South University, Changsha, China.
Hongbo ZhouDepartment of Prosthodontics, Xiangya Stomatological Hospital & School of Stomatology, Central South University, Changsha, China.
Central South University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOral squamous cell carcinoma (OSCC) is the most common type of head and neck squamous cell carcinoma with an unsatisfactory prognosis. The aim of this study was to identify potential prognostic mRNA biomarkers of OSCC based on analysis of The Cancer Genome Atlas (TCGA).

methodsExpression profiles and clinical data of OSCC patients were collected from TCGA database. Univariate Cox analysis and the least absolute shrinkage and selection operator Cox (LASSO Cox) regression were used to primarily screen prognostic biomarkers. Then multivariate Cox analysis was performed to build a prognostic model based on the selected prognostic mRNAs. Nomograms were generated to predict the individual's overall survival at 3 and 5 years. The model performance was assessed by the time-dependent receiver operating characteristic (ROC) curve and calibration plot in both training cohort and validation cohort (GSE41613 from NCBI GEO databases). In addition, machine learning was used to assess the importance of risk factors of OSCC. Finally, in order to explore the potential mechanisms of OSCC, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was completed.

resultsThree mRNAs (

conclusionA 3-mRNA signature (

Indexed as

BioinformaticsmRNAOral squamous cell carcinomaPrognosis

Identifiers

PMID31396442
PMCPMC6679650
OpenAlexW2964537634

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.