Evidence map›Paper›PMID 36072974›Full record

ArticleJournal of oncology2022

The Clinical Value of Long Noncoding RNA DDX11-AS1 as a Biomarker for the Diagnosis and Prognosis of Hepatocellular Carcinoma.

Xiaojun Luo, Yang Wang, Xi Zhang, Wenbin Liu

Open access · hybridAbstract read
In one paragraph

Article in Journal of oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.3field-weighted citation impact, top 50% 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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Making Sense of Antisense lncRNAs in Hepatocellular Carcinoma.International journal of molecular sciences · 2023
    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 at 1 institution in 1 country.

Xiaojun LuoHepatic Biliary and Pancreatic Cancer Center, Chongqing University Cancer Hospital, Chongqing, China.
Yang WangHepatic Biliary and Pancreatic Cancer Center, Chongqing University Cancer Hospital, Chongqing, China.
Xi ZhangHepatic Biliary and Pancreatic Cancer Center, Chongqing University Cancer Hospital, Chongqing, China.ORCID https://orcid.org/0000-0001-5203-776X
Wenbin LiuHepatic Biliary and Pancreatic Cancer Center, Chongqing University Cancer Hospital, Chongqing, China.ORCID https://orcid.org/0000-0003-0849-1716
Chongqing University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hepatocellular carcinoma (HCC) is a high-mortality malignant tumor with genetic and phenotypic heterogeneity, making predicting clinical outcomes challenging. The purpose of this investigation was to examine the potential usefulness of lncRNA DDX11 antisense RNA 1 (DDX11-AS1) as a biomarker for diagnosis and prognosis in hepatocellular carcinoma (HCC). The TCGA-LIHC datasets were searched for patients' clinical information and RNA-seq data, which were then collected. Relative expression levels of DDX11-AS1 in HCC tissues were determined by qRT-PCR. In order to test the sensitivity and specificity of the DDX11-AS1 receiver, receiver operating characteristic curves were utilized. The association of DDX11-AS1 expression with clinicopathological factors or prognosis was statistically analyzed. We found that the levels of DDX11-AS1 were higher in HCC specimens than in normal specimens. ROC analysis showed that DDX11-AS1 was a useful marker for discriminating HCC tissues from normal nontumor specimens. According to the results of clinical tests, a high level of DDX11-AS1 expressions was significantly related to the pathologic stage (

Identifiers

PMID36072974
PMCPMC9444391
OpenAlexW4293486785

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.