Open AccessPrognostic nomograms for predicting overall survival and cancer-specific survival of patients with very early onset colorectal cancer: a population‑based analysis
Author(s) -
Bingtian Dong,
Bingtian Dong,
Guorong Lyu
Publication year - 2022
Publication title -
bosnian journal of basic medical sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.738
H-Index - 25
eISSN - 1840-4812
pISSN - 1512-8601
DOI - 10.17305/bjbms.2021.7035
Subject(s) - nomogram , medicine , oncology , ajcc staging system , proportional hazards model , colorectal cancer , multivariate analysis , receiver operating characteristic , cohort , univariate , stage (stratigraphy) , surveillance, epidemiology, and end results , cancer , survival analysis , t stage , multivariate statistics , epidemiology , population , cancer registry , statistics , staging system , mathematics , biology , environmental health , paleontology
In contrast to the declining incidence in older populations, the incidence of very early onset colorectal cancer (VEO-CRC) patients (aged ≤40 years) has been increasing in different regions of the world. In this study, we aimed to establish nomogram models for the prognostic prediction of patients with VEO-CRC for both overall survival (OS) and cancer-specific survival (CSS). Patients diagnosed with VEO-CRC between 2010 and 2015 from the Surveillance, Epidemiology, and End Results (SEER) database were collected and randomly assigned to the training cohort and validation cohort at a ratio of 7:3 for model construction and internal validation. Using univariate and multivariate Cox regression analysis to screen important variables, which were then used to construct a nomogram. The nomogram was evaluated using calibration curves and the receiver operating characteristic (ROC) curves. A total of 3061 patients were included and randomly divided into the training cohort (n = 2145) and validation cohort (n = 916). Five independent prognostic factors, including race, grade, tumor size, AJCC stage, and AJCC T stage were all significantly identified in OS multivariate Cox regression analysis. Meanwhile in CSS, multivariate Cox regression analysis demonstrated that race, grade, tumor size, AJCC stage, AJCC T stage, AJCC N stage, and SEER stage were independent prognostic factors. The calibration plots of the established nomograms indicated high correlations between the predicted and observed results. C-index and ROC analysis implied that our nomogram model has a strong predictive ability. Moreover, nomograms also showed higher C-index values compared to tumor-node-metastasis (TNM) and SEER stages. We established and validated a simple-to-use nomogram to evaluate the 1-, 3-, and 5-year OS and CSS prognosis of patients with VEO-CRC. This tool can assist clinicians to optimize individualized treatment plans.