Evidence map›Paper›PMID 37274243›Full record

ArticleFrontiers in oncology2023

A nomogram for individually predicting the overall survival in colonic adenocarcinoma patients presenting with perineural invasion: a population study based on SEER database.

Junhong Chen, Hao Zhou, Hengwei Jin, Kai Liu

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Article in Frontiers in oncology, 2023. 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

4 authors.

Junhong ChenDepartment of Hepatobiliary and Pancreatic Surgery II, General Surgery Center, The First Hospital of Jilin University, Changchun, China.
Hao ZhouDepartment of Hepatobiliary and Pancreatic Surgery II, General Surgery Center, The First Hospital of Jilin University, Changchun, China.
Hengwei JinDepartment of Hepatobiliary and Pancreatic Surgery II, General Surgery Center, The First Hospital of Jilin University, Changchun, China.
Kai LiuDepartment of Hepatobiliary and Pancreatic Surgery II, General Surgery Center, The First Hospital of Jilin University, Changchun, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Colonic adenocarcinoma, representing the predominant histological subtype of neoplasms in the colon, is commonly denoted as colon cancer. This study endeavors to develop and validate a nomogram model designed for predicting overall survival (OS) in patients with colon cancer, specifically those presenting with perineural invasion (PNI). Methods: The Surveillance, Epidemiology, and End Results (SEER) database supplied pertinent data spanning from 2010 to 2015, which facilitated the randomization of patients into distinct training and validation cohorts at a 7:3 ratio. Both univariate and multivariate analyses were employed to construct a prognostic nomogram based on the training cohort. Subsequently, the nomogram's accuracy and efficacy were rigorously evaluated through the application of a concordance index (C-index), calibration plots, decision curve analysis (DCA), and receiver operating characteristic (ROC) curves. Results: In the training cohorts, multivariable analysis identified age, grade, T-stage, N-stage, M-stage, chemotherapy, tumor size, carcinoembryonic antigen (CEA), marital status, and insurance as independent risk factors for OS, all with Conclusion: In this study, we have devised a robust nomogram and risk stratification system to accurately predict OS in colon cancer patients exhibiting PNI. This innovative tool offers valuable guidance for informed clinical decision-making, thereby enhancing patient care and management in oncology practice.

Indexed as

colonic adenocarcinomanomogramoverall survivalperineural invasionpredict

Identifiers

PMID37274243
PMCPMC10235682

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