Related Experiment Video
Updated: Nov 8, 2025

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Comparative study of treatment options and construction nomograms to predict survival for early-stage esophageal
Ran Jia1,2, Wanyi Xiao1, Hongdian Zhang1
1Department of Esophageal Cancer, Tianjin Medical University Cancer Institute and Hospital, Key Laboratory of Cancer Prevention and Therapy of Tianjin, Tianjin's Clinical Research Center for Cancer, National Clinical Research Center of Cancer, Tianjin, China.
Background:
The aim of this study was to investigate the impact of several common treatment options on the long-term survival of patients with early-stage esophageal cancer and to construct nomograms for survival prediction.
Method:
This study was performed using the Surveillance, Epidemiology and End Results (SEER) database (2004-2015) on patients with early-stage (pT1N0M0) esophageal cancer who underwent endoscopic local therapy (ET), radiotherapy (RT), esophagectomy (ES) or neoadjuvant therapy (NT). Multivariate Cox regression was used to explore which factors influenced patient survival, and these factors were then incorporated into propensity sore matching (PSM) and the construction of nomogram plots. Kaplan-Meier analysis was used to compare whether there was a difference in long-term survival between the other three treatments and esophagectomy.
Result:
Data from 4184 patients were included in this study. Multivariate Cox regression analysis showed that age, grade, marital status, and treatment method were independent factors affecting survival. After matching, Kaplan-Meier analysis showed that the ET group had better CSS than the ES group, but no difference in OS, while the NT and RT groups had worse OS and CSS than the ES group. In the nomogram prediction model, the c-indexes of the training and validation cohorts were 0.805 and 0.794, respectively. Additionally the ROC curve (5-year AUC = 0.877) and DCA curve showed that the model had a good predictive effect.
Conclusion:
For early-stage esophageal cancer, the results of this study showed that ET is not inferior to ES. Based on the independent factors affecting prognosis identified in the study, we constructed and validated a predictive model for predicting long-term survival in patients with early-stage esophageal cancer.
More Related Videos
07:13Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
Published on: April 18, 2025
06:46Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
Published on: September 27, 2024
Related Concept Videos
Cancer Survival Analysis
Barrett Esophagus-II: Clinical Manifestations and Management
To diagnose Barrett's esophagus, healthcare providers often recommend an endoscopy for those showing symptoms of acid reflux. The procedure...
Comparing the Survival Analysis of Two or More Groups
Esophageal Varices-II: Clinical Features and Management
In the initial assessment, a thorough review of the patient's medical history is vital to identify risk factors such as liver disease, alcohol...
Barrett Esophagus-I: Introduction
This constant acid exposure transforms the esophagus's pink mucosal lining (stratified squamous epithelium) into a type of lining more...
Survival Curves
The Kaplan-Meier estimator is the most common method for constructing survival curves. This...