Development and validation of a prognostic nomogram for esophageal cancer patients based on SEER Asian population

This study aims to develop and validate a nomogram for predicting overall survival (OS) in Asian patients with Esophageal Cancer (EC). Data from Asian EC patients were collected from the Surveillance, Epidemiology, and End Results (SEER) database. The patients were randomly divided into training and validation cohorts in a 7:3 ratio. The Least Absolute Shrinkage and Selection Operator (LASSO) regression was used for initial variable selection, followed by multivariate Cox regression analysis to identify independent prognostic factors. A nomogram was subsequently constructed based on these factors. The predictive performance of the nomogram was evaluated using receiver operating characteristic (ROC) curves and calibration curves, while the clinical utility of the nomogram was assessed through decision curve analysis (DCA). The LASSO regression and multivariate Cox regression analysis identified age, sex, marital status, tumor size, M stage, surgery, and chemotherapy as independent prognostic factors. The ROC curve results demonstrated that the area under the curve (AUC) values for predicting 1-year, 3-year, and 5-year OS in the training cohort were 0.770, 0.756, and 0.783, respectively. In the validation cohort, the AUC values were 0.814, 0.763, and 0.771, respectively. Calibration curves indicated a high concordance between predicted and actual OS. The DCA demonstrated that the nomogram has significant clinical applicability. This nomogram provides reliable predictions and valuable guidance for personalized survival estimates and high-risk patient identification.

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Publication Details

Journal
Scientific Reports
Published
2024-09-14
DOI
https://doi.org/10.1038/s41598-024-72730-3
Citations
1
Primary Topic
Esophageal Cancer Research and Treatment
Type
article
Field-Weighted Citation Impact
0.57

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article

Development and validation of a prognostic nomogram for esophageal cancer patients based on SEER Asian population

Lang Qin, Xinwei Guo, Jie Tian, Pengcheng Li et al.
1 citations
Scientific Reports
Esophageal Cancer Research and Treatment
0.57
article

Development and validation of a prognostic nomogram for esophageal cancer patients based on SEER Asian population

Lang Qin, Xinwei Guo, Jie Tian, Pengcheng Li, Yu Gong, H. H. Wang, Zhenling Dou
article en
1 citations

Abstract

This study aims to develop and validate a nomogram for predicting overall survival (OS) in Asian patients with Esophageal Cancer (EC). Data from Asian EC patients were collected from the Surveillance, Epidemiology, and End Results (SEER) database. The patients were randomly divided into training and validation cohorts in a 7:3 ratio. The Least Absolute Shrinkage and Selection Operator (LASSO) regression was used for initial variable selection, followed by multivariate Cox regression analysis to identify independent prognostic factors. A nomogram was subsequently constructed based on these factors. The predictive performance of the nomogram was evaluated using receiver operating characteristic (ROC) curves and calibration curves, while the clinical utility of the nomogram was assessed through decision curve analysis (DCA). The LASSO regression and multivariate Cox regression analysis identified age, sex, marital status, tumor size, M stage, surgery, and chemotherapy as independent prognostic factors. The ROC curve results demonstrated that the area under the curve (AUC) values for predicting 1-year, 3-year, and 5-year OS in the training cohort were 0.770, 0.756, and 0.783, respectively. In the validation cohort, the AUC values were 0.814, 0.763, and 0.771, respectively. Calibration curves indicated a high concordance between predicted and actual OS. The DCA demonstrated that the nomogram has significant clinical applicability. This nomogram provides reliable predictions and valuable guidance for personalized survival estimates and high-risk patient identification.

Scientific ReportsVol. 14(1)
Anhui University of Science and Technology (CN), Taixing People's Hospital (CN), Huainan Normal University (CN)
Bengbu Medical College, China Health Promotion Foundation
Openalex Percentile: Top 30%
Esophageal Cancer Research and Treatment
0.57
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