Evidence map›Paper›PMID 32946170›Full record

ArticleCancer medicine2020

A prognostic model composed of four long noncoding RNAs predicts the overall survival of Asian patients with hepatocellular carcinoma.

Xuefeng Gu, Hongbo Li, Ling Sha, Wei Zhao

Abstract read
In one paragraph

Article in Cancer medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

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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

4 authors.

Xuefeng GuMedical School, Southeast University, Nanjing, Jiangsu, China.
Hongbo LiDepartment of Hepatology, Infectious Diseases Hospital Affiliated with Soochow University, Suzhou, Jiangsu, China.
Ling ShaDepartment of Neurology, Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China.
Wei ZhaoMedical School, Southeast University, Nanjing, Jiangsu, China.ORCID 0000-0001-5698-4844

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Based on accumulating evidence, long noncoding RNAs (lncRNAs) are potential biomarkers and therapeutic targets for many diseases, including tumors. In this study, we consulted The Cancer Genome Atlas (TCGA) database to explore the functions and modulatory mechanisms of lncRNAs as competing endogenous RNAs (ceRNAs) in hepatocellular carcinoma (HCC) in Asian patients and constructed a risk scoring system composed of four lncRNAs (SNHG1, STEAP3-AS1, RUSC1-AS1, and SNHG3) to predict the outcomes of Asian patients with HCC. The prognostic value of this risk model was validated in the internal validation cohort (n = 157). The stratified survival analysis revealed good performance for the risk model in stratifying clinical features. According to the Cox proportional hazard regression analysis, the four-lncRNA risk model is an independent prognostic model for Asian patients with HCC. Finally, we developed a nomogram that integrates prognostic signals and other clinical information to predict 1-, 3-, and 5-year overall survival rates. In conclusion, the prognostic lncRNAs identified in our study exerted potential biological effects on the development of HCC. The risk scoring model based on four lncRNAs may be an effective classification tool for assessing the prognosis of Asian patients with HCC.

Indexed as

Adaptor Proteins, Signal TransducingAsian PeopleCarcinoma, HepatocellularCell Cycle ProteinsFemaleHumansLiver NeoplasmsMaleMicroRNAsMiddle AgedOxidoreductasesPrognosisRNA, Long NoncodingRNA, MessengerSurvival AnalysisSurvival RateAdaptor Proteins, Signal TransducingCell Cycle Proteinslong non-coding RNA SNHG1, humanMicroRNAsOxidoreductasesRNA, Long NoncodingRNA, MessengerRUSC1 protein, humanSNHG32 lncRNA, humanSTEAP3 protein, humanceRNAhepatocellular carcinomalncRNAoverall survivalrisk scoreTCGA

Identifiers

PMID32946170
PMCPMC7433813

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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.