Evidence map›Paper›PMID 35242861›Full record

ArticleAnnals of translational medicine2022

Prediction of distant metastasis and survival prediction of gastric cancer patients with metastasis to the liver, lung, bone, and brain: research based on the SEER database.

Zikai Lin, Runchen Wang, Youtao Zhou, Qixia Wang, Cui-Yan Yang, Bo-Cun Hao, Chuan-Feng Ke

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Article in Annals of translational medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
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1 · What the graph read from it

What it found

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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.

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3 · Its place in the literature

Who cites it

21 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Zikai Lin *Department of Gastrointestinal Surgery, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Runchen Wang *Department of Gastrointestinal Surgery, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Youtao Zhou *Department of Gastrointestinal Surgery, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Qixia WangDepartment of Gastrointestinal Surgery, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Cui-Yan YangDepartment of Gastrointestinal Surgery, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Bo-Cun HaoDepartment of Gastrointestinal Surgery, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Chuan-Feng KeDepartment of Gastrointestinal Surgery, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGastric cancer (GC) is a globally important disease. It is the 5th most common malignancy and the 4th most common cause of death from cancer in the world. Patients with GC are often at an advanced stage when they are first diagnosed, and their overall prognosis is poor due to locally advanced and distant metastasis. This study sought to establish a predictive model of GC distant metastasis and survival that can be used to guide individualized treatment.

methodsPatients diagnosed with GC from the Surveillance, Epidemiology, and End Results database were enrolled in the study. Univariate and multivariate logistic regression analyses were used to identify risk and prognostic factors for GC patients with distant metastasis. The factors were then used to construct nomograms to predict the probability of distant metastasis and the survival time of GC patients. Receiver operating characteristic (ROC) curve and decision curve analyses were used to verify the prediction ability of the nomograms.

resultsWe established a comprehensive nomogram to predict the survival time of GC patients and 4 nomograms to predict distant metastasis. Nomograms could help oncologists to formulate treatment strategies and provide hospice care under an overall management model.

conclusionsEstablishing a prediction model for distant metastasis and the survival of GC patients is of great clinical significance. The prediction of distant metastasis could help clinicians to make individualized assessments of patients and formulate individualized examination measures. Survival prediction models could help oncologists to formulate good treatment strategies and provide hospice care.

Indexed as

decision curve analysis (DCA)distant metastasisGastric cancer (GC)nomogramoverall survival (OS)

Identifiers

PMID35242861
PMCPMC8825534

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