ArticleJournal of cancer research and clinical oncology2023
Construction and validation of a prognostic nomogram for predicting cancer-specific survival in patients with intermediate and advanced colon cancer after receiving surgery and chemotherapy.
Article in Journal of cancer research and clinical oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Development and validation of predictive nomograms for survival in early-onset colon cancer patients with II-III stage across various tumor sites.Translational cancer research · 2025Article
- Development and validation of cancer-specific survival prediction nomogram for patients with T4 stage colon cancer after surgical resection: a population-based study.International journal of colorectal disease · 2025Article
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8 authors.
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Abstract
backgroundExisting predictive models often focus solely on overall survival (OS), neglecting the bias that other causes of death might introduce into survival rate predictions. To date, there is no strict predictive model established for cancer-specific survival (CSS) in patients with intermediate and advanced colon cancer after receiving surgery and chemotherapy.
methodsWe extracted the data from the Surveillance, Epidemiology, and End Results (SEER) database on patients with stage-III and -IV colon cancer treated with surgery and chemotherapy between 2010 and 2015. The cancer-specific survival (CSS) was assessed using a competitive risk model, and the associated risk factors were identified via univariate and multivariate analyses. A nomogram predicting 1-, 3-, and 5-year CSS was constructed. The c-index, area under the curve (AUC), and calibration curve were adopted to assess the predictive performance of the model. Additionally, the model was externally validated.
resultsA total of 18 risk factors were identified by univariate and multivariate analyses for constructing the nomogram. The AUC values of the nomogram for the 1-, 3-, and 5-year CSS prediction were 0.831, 0.842, and 0.848 in the training set; 0.842, 0.853, and 0.849 in the internal validation set; and 0.815, 0.823, and 0.839 in the external validation set. The C-index were 0.826 (se: 0.001), 0.836 (se: 0.002) and 0.763 (se: 0.013), respectively. Moreover, the calibration curve showed great calibration.
conclusionThe model we have constructed is of great accuracy and reliability, and can help physicians develop treatment and follow-up strategies that are beneficial to the survival of the patients.
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