Evidence map›Paper›PMID 31422414›Full record

ArticleMedical science monitor : international medical journal of experimental and clinical research2019

A 5-Gene Prognostic Combination for Predicting Survival of Patients with Gastric Cancer.

Liang Song, Xiao-Yan Wang, Xiao-Feng He

Open access · hybridAbstract read
In one paragraph

Article in Medical science monitor : international medical journal of experimental and clinical research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
0.3field-weighted citation impact, top 47% 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

4 citing papers in PubMed, 1 synthesis or guideline pooled it, 5 citations in OpenAlex.

  1. Systematic Review of Prognostic Gene Signature in Gastric Cancer Patients.Frontiers in bioengineering and biotechnology · 2020
    Pooled it
  2. Article
  3. Article
  4. Article
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 at 2 institutions in 1 country.

Liang SongEndoscopy Room, Heping Hospital Affiliated to Changzhi Medical College, Changzhi, Shanxi, China (mainland).
Xiao-Yan WangDepartment of Epidemiology and Health Statistics, Basic Medical College of Zhejiang University of Traditional Chinese Medicine, Hangzhou, Zhejiang, China (mainland).
Xiao-Feng HeDepartment of Science and Education, Heping Hospital Affiliated to Changzhi Medical College, Changzhi, Shanxi, China (mainland).
Changzhi Medical College · CNZhejiang University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND The aim of the study was to identify a multigene prognostic factor in patients with gastric cancer (GC). MATERIAL AND METHODS Random survival forest (RSF) was performed to screen survival-related genes and develop a multigene combination based on the cumulative hazard function of each GC patient in TCGA-STAD and GSE15459. Kaplan-Meier curve and univariate and multivariable Cox proportional hazards regression model were applied to evaluate the prognostic performance of the 5-gene combination. C-index was used to compare the prognostic performance of the 5-gene combination and another 9-gene signature in GC. Gene set enrichment analysis (GSEA) was conducted. RESULTS We obtained 19 survival-related genes through univariate Cox proportional hazards analysis in the training set, 5 of which were identified and were used to develop a 5-gene combination through RSF. Patients in the 5-gene combination low-risk group had better overall survival (OS) than those in the 5-gene combination high-risk group, and the 5-gene combination was demonstrated to be an independent prognostic factor in patients with GC. The 5-gene combination outperformed the 9-gene signature in predicting the OS of GC patients, and it might affect the prognosis of GC patients through E2F signaling, MYC signaling, and G2M checkpoint. CONCLUSIONS We introduce a 5-gene combination that can predict the survival of GC patients and might be an independent prognostic factor in GC.

Indexed as

AdultAgedAged, 80 and overBiomarkers, TumorChinaDatabases, GeneticFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansKaplan-Meier EstimateMaleMiddle AgedPrognosisProportional Hazards ModelsRisk FactorsBiomarkers, Tumor

Identifiers

PMID31422414
PMCPMC6713029
OpenAlexW2967691671

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.