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Updated: Jun 8, 2025

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
Published on: September 27, 2024
A competing-risk nomogram for predicting gastric cancer-specific survival in patients over 70 years: A SEER-based
Maorun Zhang1, Xuliang Yang2, Jinyan Jia1
1Department of General Surgery, Tianjin Medical University General Hospital, Tianjin 300052, China; Tianjin Key Laboratory of Precise Vascular Reconstruction and Organ Function Repair, Tianjin 300052, China; Tianjin General Surgery Institute, Tianjin 300052, China.
Background:
Cancer-specific survival in older patients with gastric cancer is competitively affected by death from other causes. This study aimed to investigate cancer-specific survival and associated risk factors by competing-risk analysis in older patients with gastric cancer.
Methods:
The data of this study are from the SEER database, using univariable and multivariable analysis of competitive risk model to weaken the impact of competitive events, explore the risk factors of cancer-specific survival, and developed a nomogram model. Then, the performance of the model is verified by C-index, ROC curve, calibration curve and DCA, and the new model is compared with the traditional TNM stage by NRI and IDI.
Results:
Our study encompassed a total of 8183 patients, with 5731 in the training cohort and 2452 in the validation cohort. Univariable and multivariable analysis showed that age, years of diagnosis, race, site, SEER stage, TNM stage, surgery, radiation or chemotherapy, LNE, tumor grade and size are independent risk factors for cancer-specific survival in older patients with gastric cancer. Based on the risk factors, we developed a diagram model to predict cancer-specific survival. C-index, ROC curve, calibration curve and DCA also show good results. We compared the new model with the traditional TNM stage model, and the NRI and IDI showed the new model has been significantly improved.
Conclusion:
This study developed a nomogram to predict the cancer-specific survival of older patients with gastric cancer, which can accurately predict the prognosis and contribute to clinical treatment decision-making.
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