Evidence map›Paper›PMID 30328513›Full record

ArticleJournal of cancer research and clinical oncology2019

A novel prognostic signature of seven genes for the prediction in patients with thymoma.

Qiang Li, Yan-Ling Su, Wei-Xi Shen

Abstract read
In one paragraph

Article in Journal of cancer research and clinical oncology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

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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

8 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. The Molecular Landscape of Thymic Epithelial Tumors: A Comprehensive Review.International journal of molecular sciences · 2024
    Review
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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

3 authors.

Qiang LiDepartment of Oncology, Shenzhen Hospital, Southern Medical University, No. 1333, Xinhu Road, Bao'an District, Shenzhen, 518000, Guangdong Province, China. 110184356@qq.com.ORCID http://orcid.org/0000-0001-9910-7606
Yan-Ling SuOutpatient Department, National Cancer Center, Cancer Hospital and Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, Guangdong Province, China.
Wei-Xi ShenDepartment of Oncology, Shenzhen Hospital, Southern Medical University, No. 1333, Xinhu Road, Bao'an District, Shenzhen, 518000, Guangdong Province, China.

Funding

Sanming Project of Medicine in Shenzhen SZSM201612023
6 · The paper itself

Abstract

purposeA thymoma is a tumor arising from the epithelium of the thymus, mostly occurring in the anterior mediastinum. The incidence of this disease is low and research progress in this field is slow. Consequently, there is an urgent need to investigate the correlation between molecular regulation and the prediction of survival and prognosis in patients with thymoma.

methodsWe collected thymoma datasets from The Cancer Genome Atlas (TCGA). Differentially expressed genes (DEGs) of TCGA datasets were then determined using R software. A gene signature was obtained by screening prognostic DEGs from the TCGA datasets using univariate and multivariate Cox survival analysis. The summation of the weighted expression levels was calculated as a risk score, which could then be used to predict the survival rate and prognosis of patients with thymoma. The validity of this model was verified by the analysis of receiver operating characteristic (ROC) curves and area under the curve (AUC).

resultsIn total, 297 DEGs were identified from the integrated results of TCGA datasets. A seven-gene signature, along with a regression model of prognostic risk, was obtained by Cox survival analysis. The expression levels of the seven genes were then weighted and summed to calculate the risk score for each sample. Patients were effectively divided into high- and low-risk groups using the median risk score (P < 0.05). ROC analysis showed that this Cox regression model was effective in predicting the prognosis of patients with thymus tumors (AUC = 0.983, P < 0.05).

conclusionFor the first time, we identified an effective seven-gene signature in patients with thymic tumors. In the future, the risk and prognosis of patients can be preliminarily assessed using this model, although further testing is required to improve rigor.

Indexed as

Atlases as TopicBiomarkers, TumorDatasets as TopicGene Expression Regulation, NeoplasticHumansPrognosisProportional Hazards ModelsReproducibility of ResultsRisk AssessmentSignal TransductionSurvival AnalysisThymomaThymus NeoplasmsBiomarkers, TumorGene signaturePrognostic signatureRisk scoreThymoma

Identifiers

PMID30328513
PMCPMC6326008

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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.