Evidence map›Paper›PMID 29088749›Full record

ArticleOncotarget2017

Identification and validation of a prognostic 9-genes expression signature for gastric cancer.

Zhiqiang Wang, Gongxing Chen, Qilong Wang, Wei Lu, Meidong Xu

Abstract read
In one paragraph

Article in Oncotarget, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

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

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

  1. Systematic Review of Prognostic Gene Signature in Gastric Cancer Patients.Frontiers in bioengineering and biotechnology · 2020
    Pooled it
  2. Article
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  5. Lysosomal-associated membrane protein family member 5 promotes the metastatic potential of gastric cancer cells.Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association · 2022
    Article
  6. Identification and Validation of a Novel Prognostic Gene Model for Colorectal Cancer.Computational and mathematical methods in medicine · 2022
    Article
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  15. A 5-Gene Prognostic Combination for Predicting Survival of Patients with Gastric Cancer.Medical science monitor : international medical journal of experimental and clinical research · 2019
    Article
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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.

Zhiqiang WangEndoscopy Center and Endoscopy Research Institute, Zhongshan Hospital, Fudan University, Shanghai, China.
Gongxing ChenThe Laboratory Center of Medical School of Hangzhou Normal University, Hangzhou, China.
Qilong WangEndoscopy Center and Endoscopy Research Institute, Zhongshan Hospital, Fudan University, Shanghai, China.
Wei LuDepartment of General Surgery, Xinhua Hospital, Shanghai JiaoTong University, School of Medicine, Shanghai, China.
Meidong XuEndoscopy Center and Endoscopy Research Institute, Zhongshan Hospital, Fudan University, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gastric cancer (GC) is a common malignant tumor with high incidence and mortality. Reasonable assessment of prognosis is essential to improve the outcomes of patients. In this study, we constructed and validated a prognostic gene model to evaluate the risks of GC patients. To identify the differentially expressed genes between GC patients and controls, we extracted Gene expression profiles of GC patients (N=432) from Gene Expression Omnibus database and then stable signature genes by using Robust likelihood-based modeling with 1000 iterations. Unsupervised hierarchical clustering of all samples was performed basing on the characteristics of gene expressions. Meanwhile, the differences between the clusters were analyzed by Kaplan Meier survival analysis. A 9-genes model was obtained (frequency = 999; p=1.333628e

Indexed as

clustering analysisgastric cancerprognostic modelsurvival analysis

Identifiers

PMID29088749
PMCPMC5650304

What OpenQuestion holds

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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.