Nomogram predicting cancer-specific survival in elderly patients with stages I–III colon cancer

Abstract

Aim: This study aims to establish and validate an effective nomogram to predict cancer-specific survival (CSS) in elderly patients with stages I–III colon cancer.

Methods: The data of elderly colon cancer patients with stages I–III were enrolled from the Surveillance, Epidemiology, and End Results database (SEER) between 2010 and 2015. The eligible patients were randomly divided into a training cohort and a validation cohort (ratio 1:1). All predictors of cancer-specific survival were determined by Cox regression. The concordance index (C-index) and calibration curves were used for validation of nomograms. Decision curve analysis (DCA) was performed to evaluate the clinical net benefit of the nomogram.

Results: Cox hazard analysis in the training cohort indicated that grade, tumor stage, node stage, colectomy, and CEA were independent predictors of CSS. Nomogram was constructed based on these predictors. The C-index of nomograms for CSS was 0.728 (95%CI: 0.7133–0.7427), and were superior to that of AJCC TNM Stage (C-index: 0.625, 95%CI: 0.6093–0.6406). The calibration curves showed satisfactory consistency between actual observation and nomogram-predicted CSS probabilities. The validation cohort demonstrated similar results. The DCA showed high net benefit of nomogram in a clinical context. The population was divided into three groups based on the scores of the nomogram, and the survival analysis showed that this prognostic stratification was statistically significant (p < 0.01).

Conclusion: The nomograms showed significant accuracy in predicting 1-, 3-, and 5-year CSS in elderly patients with stages I–III colon cancer and may be helpful inpatient counseling clinical decision guidance.

Keywords:

• SEER database
• colon cancer
• nomogram
• elderly patients
• prognostic model

Acknowledgments

The authors thank SEER program for public access to the database.

Author contributions

Peilin Zheng and Zhikang Chen designed the research; Peilin Zheng, Chen Lai and Weimin Yang analyzed data; Peilin Zheng wrote the draft. All members have proofread the article.

Disclosure statement

The authors have no conflict of interest to disclose.