Evidence map›Paper›PMID 41281496›Full record

ArticleWorld journal of gastrointestinal oncology2025

Construction of a prognostic model for colorectal cancer liver metastasis: A retrospective study based on population data.

Mian-Jiao Xie, Jia-Jun Li, Ya-Jie Guo, Qi Wang, Zhao-Bang Tan, Yun-Long Li, Ji-Peng Li

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Article in World journal of gastrointestinal oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Mian-Jiao XieDepartment of Experimental Surgery, Xijing Hospital, Air Force Medical University, Xi'an 710032, Shaanxi Province, China.
Jia-Jun LiDepartment of Gastrointestinal Surgery, The Second Affiliated Hospital of Chengdu Medical College, Nuclear Industry 416 Hospital, Chengdu 610000, Sichuan Province, China.
Ya-Jie GuoDepartment of Digestive Surgery, Xijing Hospital of Digestive Diseases, Air Force Medical University, Xi'an 710032, Shaanxi Province, China.
Qi WangDepartment of Digestive Surgery, Xijing Hospital of Digestive Diseases, Air Force Medical University, Xi'an 710032, Shaanxi Province, China.
Zhao-Bang TanDepartment of Digestive Surgery, Xijing Hospital of Digestive Diseases, Air Force Medical University, Xi'an 710032, Shaanxi Province, China.
Yun-Long LiDepartment of Digestive Surgery, Xijing Hospital of Digestive Diseases, Air Force Medical University, Xi'an 710032, Shaanxi Province, China.
Ji-Peng LiDepartment of Experimental Surgery, Xijing Hospital, Air Force Medical University, Xi'an 710032, Shaanxi Province, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundColorectal cancer (CRC) is a prevalent gastrointestinal malignancy with a typically unfavorable prognosis following the onset of liver metastases.

aimTo develop and validate a new clinical prediction model to accurately forecast overall survival (OS) in CRC patients following surgical treatment for liver metastasis.

methodsThis study included 1059 patients diagnosed with CRC liver metastases (CRLM) at the Xijing Hospital between 2010 and 2022. The patients were randomly divided into training and validation cohorts at a 7:3 ratio. Key clinical predictors were identified using least absolute shrinkage and selection operator (LASSO) regression combined with a Cox proportional hazards model, leading to the establishment of a prediction model and preparation of a nomogram to enhance its clinical utility. Decision curve analysis (DCA) and Kaplan-Meier survival analysis were employed to evaluate the precision and predictive performance of the model.

resultsThe LASSO-Cox regression analysis revealed multiple pivotal clinical biomarkers significantly linked to CRLM, including gamma-glutamyl transferase levels, blood chloride concentration, activated partial thromboplastin time, N stage, and vascular invasion. The model's receiver operating characteristic curve area under the curve exceeded 0.7 for both the training and validation groups with moderate-to-good predictive accuracy. Furthermore, DCA validated the nomogram's effectiveness for OS prediction. Kaplan-Meier risk stratification demonstrated markedly improved OS among patients classified as low-risk compared to those categorized as high-risk (

conclusionThe nomogram prediction model constructed in this study has good predictive value and can effectively assess the survival rate of patients with CRLM.

Indexed as

Colorectal cancer liver metastasisMonitoringNomogramOverall survivalSurvival prediction model

Identifiers

PMID41281496
PMCPMC12635695

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