Research Paper Volume 13, Issue 1 pp 477—492
Development and validation of prognostic nomograms for early-onset locally advanced colon cancer
- 1 Department of Gastrointestinal Surgery, Xiangya Hospital, Central South University, Changsha, China
- 2 Department of Rheumatology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
- 3 Department of Cardiology, Xiangya Hospital, Central South University, Changsha, China
- 4 Department of Thoracic surgery, Fujian Provincial Hospital, Fuzhou, China
Received: April 14, 2020 Accepted: October 20, 2020 Published: December 3, 2020https://doi.org/10.18632/aging.202157
How to Cite
Copyright: © 2020 Li et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Background: The incidence of colorectal cancer in patients younger than 50 years has been increasing in recent years.
Objective: Develop and validate prognostic nomograms predicting overall survival (OS) and cancer-specific survival (CSS) for early-onset locally advanced colon cancer (EOLACC) based on the Surveillance, Epidemiology, and End Results (SEER) database.
Results: The entire cohort comprised 13,755 patients with EOLACC. The nomogram predicting OS for EOLACC displayed that T stage contributed the most to prognosis, followed by N stage, regional nodes examined (RNE) and surgery. The nomogram predicting CSS for EOLACC demonstrated similar results. Various methods identified the discriminating superiority of the nomograms. X-tile software was used to classify patients into high-risk, medium-risk, and low-risk according to the risk score of the nomograms. The risk stratification effectively avoided the survival paradox.
Conclusions: We established and validated nomograms for predicting OS and CSS based on a national cohort of almost 13,000 EOLACC patients. The nomograms could effectively solve the issue of survival paradox of the AJCC staging system and be an excellent tool to integrate the clinical characteristics to guide the therapeutic choice for EOLACC patients.
Methods: Nomograms were constructed based on the SEER database and the Cox regression model.