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Updated: Jul 18, 2025
Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
Published on: September 27, 2024
Development and external validation of a nomogram predicting overall survival for Gastric adenocarcinoma patients
Zhipeng He1,2, Feng Lin2,3, Tingting Cheng2
1Department of General Surgery, The Second Affiliated Hospital of Nanchang University, Nanchang, China.
Purpose:
The aim of this study was to develop and externally validate a nomogram to accurately predict the overall survival (OS) of patients with gastric adenocarcinoma who underwent radical gastrectomy.
Materials And Methods:
A total of 3492 patients with gastric adenocarcinoma who underwent radical gastrectomy from 2012 to 2017 were included as the training cohort. Survival analysis was performed via Kaplan Meier method and log-rank test. Independent postoperative prognostic factors in patients with gastric adenocarcinoma were analyzed using univariate and multifactorial COX analysis methods. The prognosis nomogram was established in the training cohort and verified externally in the Surveillance, Epidemiology and End Results (SEER) database.
Results:
According to the univariate and multifactorial COX analyses, metastatic lymph node ratio (MLNR) and five other independent prognostic factors (age at surgery, type of gastrectomy, tumor size, T stage, and pathological grade) were included in the prognostic nomogram. The nomogram had better prognostic predictive ability than the American Joint Committee on Cancer (AJCC) TNM staging in both the training (C-index: 0.736 VS. 0.668) and external validation cohort (C-index: 0.712 VS. 0.627). The calibration plots showed that the predicted survival rate was in good agreement with the actual survival rate. And the decision curve analysis (DCA) curves revealed that nomogram showed stronger ability in predicting 1-year, 3-year, and 5-year OS.
Conclusion:
This study estimated the excellent prognostic predictive power and clinical application potential of the MLNR-based nomogram, which may be used to facilitate postoperative clinical treatment decisions and potentially improve patient survival outcomes.
