Evidence map›Paper›PMID 37900243›Full record

ArticleWorld journal of clinical cases2023

Prognostic model of hepatocellular carcinoma based on cancer grade.

Guo-Xin Zhang, Xiao-Sheng Ding, You-Li Wang

Abstract read
In one paragraph

Article in World journal of clinical cases, 2023. 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.

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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

3 authors.

Guo-Xin ZhangDepartment of General Surgery, Aviation General Hospital, Beijing 100010, China.
Xiao-Sheng DingDepartment of Oncology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China.
You-Li WangDepartment of General Surgery, Aviation General Hospital, Beijing 100010, China. stage9999@sina.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHepatocellular carcinoma (HCC) is the most common type of primary liver cancer. With highly invasive biological characteristics and a lack of obvious clinical manifestations, HCC usually has a poor prognosis and ranks fourth in cancer mortality. The aetiology and exact molecular mechanism of primary HCC are still unclear.

aimTo select the characteristic genes that are significantly associated with the prognosis of HCC patients and construct a prognosis model of this malignancy.

methodsBy comparing the gene expression levels of patients with different cancer grades of HCC, we screened out differentially expressed genes associated with tumour grade. By protein-protein interaction (PPI) network analysis, we obtained the top 2 PPI networks and hub genes from these differentially expressed genes. By using least absolute shrinkage and selection operator Cox regression, 13 prognostic genes were selected for feature extraction, and a prognostic risk model of HCC was established.

resultsThe model had significant prognostic ability in HCC. We also analysed the biological functions of these prognostic genes.

conclusionBy comparing the gene profiles of patients with different stages of HCC, We have constructed a prognosis model consisting of 13 genes that have important prognostic value. This model has good application value and can be explained clinically.

Indexed as

Alpha-fetoproteinBioinformaticsHepatocellular carcinomaPrognostic model

Identifiers

PMID37900243
PMCPMC10600993

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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.