Evidence map›Paper›PMID 32878427›Full record

ArticleCancer research and treatment2021

An Innovative Prognostic Model Based on Four Genes in Asian Patient with Gastric Cancer.

Jiahui Chen, Anqiang Wang, Jun Ji, Kai Zhou, Zhaode Bu, Guoqing Lyu, Jiafu Ji

Abstract read
In one paragraph

Article in Cancer research and treatment, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

14 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

7 authors.

Jiahui ChenDepartment of Gastrointestinal Surgery, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital and Institute, Beijing, China.
Anqiang WangDepartment of Gastrointestinal Surgery, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital and Institute, Beijing, China.
Jun JiDepartment of Gastrointestinal Surgery, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China.
Kai ZhouDepartment of Gastrointestinal Surgery, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital and Institute, Beijing, China.
Zhaode BuDepartment of Gastrointestinal Surgery, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital and Institute, Beijing, China.
Guoqing LyuDepartment of Gastrointestinal Surgery, Peking University Shenzhen Hospital, Shenzhen, China.
Jiafu JiDepartment of Gastrointestinal Surgery, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital and Institute, Beijing, China.

Funding

Beijing Municipal Science and Technology Project D131100005313010National Key Technology Support Program 2014BA109B02National Science Foundation for Young Scientists of China 81802735San Ming Project of Shenzhen city SZSM201612051
6 · The paper itself

Abstract

purposeGastric cancer (GC) has substantial biological differences between Asian and non-Asian populations, which makes it difficult to have a unified predictive measure for all people. We aimed to identify novel prognostic biomarkers to help predict the prognosis of Asian GC patients. MATERIALS AND

methodsWe investigated the differential gene expression between GC and normal tissues of GSE66229. Univariate, multivariate and Lasso Cox regression analyses were conducted to establish a four-gene-related prognostic model based on the risk score. The risk score was based on a linear combination of the expression levels of individual genes multiplied by their multivariate Cox regression coefficients. Validation of the prognostic model was conducted using The Cancer Genome Atlas (TCGA) database. A nomogram containing clinical characteristics and the prognostic model was established to predict the prognosis of Asian GC patients.

resultsFour genes (RBPMS2, RGN, PLEKHS1, and CT83) were selected to establish the prognostic model, and it was validated in the TCGA Asian cohort. Receiver operating characteristic analysis confirmed the sensitivity and specificity of the prognostic model. Based on the prognostic model, a nomogram containing clinical characteristics and the prognostic model was established, and Harrell's concordance index of the nomogram for evaluating the overall survival significantly higher than the model only focuses on the pathologic stage (0.74 vs. 0.64, p < 0.001).

conclusionThe four-gene-related prognostic model and the nomogram based on it are reliable tools for predicting the overall survival of Asian GC patients.

Indexed as

Asian PeopleFemaleHumansMalePrognosisStomach NeoplasmsNomogramsOverall survivalPrognostic modelRisk scoreStomach neoplasms

Identifiers

PMID32878427
PMCPMC7812008

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