Nomogram for Predicting Early Death in Patients with Metastatic Colon Cancer Based on SEER Database

Objective To construct a Nomogram model that can accurately predict early death of metastatic colon cancer (mCC).

Methods A total of 6 669 patients from the SEER database were identified using inclusion and exclusion criteria. Multivariate logistic regression was used to identify risk factors for early mortality and to construct a Nomogram. The predictive performance of the Nomogram was evaluated by C-index, calibration curve, and decision curve analysis (DCA).

Results Primary tumor location, differentiation grade, T stage, M stage, bone metastases, brain metastases, CEA, tumor size, age and marital status were independent factors for early death in patients with mCC. A Nomogram was constructed based on these variables. The C-index and the calibration curve of the Nomogram showed the good predictive ability of the nomogram. DCA showed that the Nomogram had a superior clinical net benefit in predicting early death compared with TNM stage.

Conclusion The developed Nomogram has good predictive ability and can help guide clinicians to identify patients with high-risk mCC for individualized diagnosis and treatment.