Evidence map›Paper›PMID 30864737›Full record

ArticleOncology reports2019

Analysis of microRNA expression profiles reveals a 5‑microRNA prognostic signature for predicting overall survival time in patients with gastric adenocarcinoma.

Ruihong Zhao, Lei Zhao, Xu Xu, Hong Xu

Abstract readValidation Study
In one paragraph

Article in Oncology reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
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

4 authors.

Ruihong ZhaoDepartment of Gastroenterology, The First Hospital of Jilin University, Changchun, Jilin 130021, P.R. China.
Lei ZhaoDepartment of Medical Insurance Management, The First Hospital of Jilin University, Changchun, Jilin 130021, P.R. China.
Xu XuDepartment of Gastroenterology, The First Hospital of Jilin University, Changchun, Jilin 130021, P.R. China.
Hong XuDepartment of Gastroenterology, The First Hospital of Jilin University, Changchun, Jilin 130021, P.R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

There is growing evidence supporting dysregulated microRNAs (miRNAs) as potential prognostic biomarkers in cancer. The present study aimed to identify an miRNA model set with prognostic power for patients with gastric adenocarcinoma. miRNA‑seq data from 155 patients and 37 controls were downloaded from The Cancer Genome Atlas (TCGA) database for a comprehensive analysis of miRNA expression profiles and were used as training data. A total of 5 prognostic miRNAs, which have not been previously reported, were identified using univariate and multivariate Cox regression analyses. A separate 155‑patient TCGA cohort was used as a validation set for evaluation of the risk model. Patients in the training set were assigned into high‑ and low‑risk groups according to the 5‑miRNA signature risk scores. Kaplan‑Meier survival analyses demonstrated that patients with high risk scores had significantly shorter survival times than those with low risk scores. The risk model validation confirmed the prognostic ability of this 5‑miRNA signature in predicting the risk status of patients. Stratification analysis for clinical prognostic variables demonstrated recurrence and age were significant prognostic factors in the low‑ and high‑risk groups, respectively. In conclusion, the present 5‑miRNA signature is a potential independent risk factor for patient outcomes. The risk model based on the 5‑miRNA signature performed well in predicting overall survival time in patients with gastric adenocarcinoma.

Indexed as

AdenocarcinomaAgedBiomarkers, TumorCase-Control StudiesCohort StudiesDatabases, GeneticDatasets as TopicFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansKaplan-Meier EstimateMaleMicroRNAsMiddle AgedModels, BiologicalBiomarkers, TumorMicroRNAs

Identifiers

PMID30864737
PMCPMC6448084

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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.