Evidence map›Paper›PMID 39351249›Full record

ArticleWorld journal of gastroenterology2024

Construction and validation of a pancreatic cancer prognostic model based on genes related to the hypoxic tumor microenvironment.

Fan Yang, Na Jiang, Xiao-Yu Li, Xing-Si Qi, Zi-Bin Tian, Ying-Jie Guo

Abstract readValidation Study
In one paragraph

Article in World journal of gastroenterology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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3 · Its place in the literature

Who cites it

4 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

6 authors.

Fan YangDepartment of Gastroenterology, The Affiliated Hospital of Qingdao University, Qingdao 266000, Shandong Province, China.
Na JiangDepartment of Gastroenterology, The Affiliated Hospital of Qingdao University, Qingdao 266000, Shandong Province, China.
Xiao-Yu LiDepartment of Gastroenterology, The Affiliated Hospital of Qingdao University, Qingdao 266000, Shandong Province, China.
Xing-Si QiDepartment of Gastroenterology, The Affiliated Hospital of Qingdao University, Qingdao 266000, Shandong Province, China.
Zi-Bin TianDepartment of Gastroenterology, The Affiliated Hospital of Qingdao University, Qingdao 266000, Shandong Province, China.
Ying-Jie GuoDepartment of Gastroenterology, The Affiliated Hospital of Qingdao University, Qingdao 266000, Shandong Province, China. guoyingjie305@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPancreatic cancer is one of the most lethal malignancies, characterized by poor prognosis and low survival rates. Traditional prognostic factors for pancreatic cancer offer inadequate predictive accuracy, often failing to capture the complexity of the disease. The hypoxic tumor microenvironment has been recognized as a significant factor influencing cancer progression and resistance to treatment. This study aims to develop a prognostic model based on key hypoxia-related molecules to enhance prediction accuracy for patient outcomes and to guide more effective treatment strategies in pancreatic cancer.

aimTo develop and validate a prognostic model for predicting outcomes in patients with pancreatic cancer using key hypoxia-related molecules.

methodsThis pancreatic cancer prognostic model was developed based on the expression levels of the hypoxia-associated genes

resultsThe prognostic model demonstrated significant predictive value, with the risk score showing a strong correlation with clinical features: It was significantly associated with tumor grade (G) (

conclusionThe prognostic model based on hypoxia-related genes effectively predicts pancreatic cancer outcomes with improved accuracy over traditional factors and can guide treatment selection based on risk assessment.

Indexed as

Biomarkers, TumorGene Expression Regulation, NeoplasticPancreatic NeoplasmsTumor MicroenvironmentAgedCell Line, TumorFemaleGene Expression ProfilingHumansMaleMiddle AgedNeoplasm GradingPredictive Value of TestsPrognosisRisk AssessmentTumor HypoxiaBiomarkers, TumorHypoxiaImmune microenvironmentMetabolism pathwayPancreatic cancerPrognostic model

Identifiers

PMID39351249
PMCPMC11439118

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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.