Jiqing Li1, Jianhua Gu1, Xiaotian Ma1, Xiao Li2, Xiaojuan Liu1, Fengling Kang1, Fuzhong Xue1. 1. Department of Epidemiology and Biostatistics, School of Public Health, Shandong University, Jinan, Shandong, China. 2. Department of Gastroenterology, Shandong Provincial Hospital, Jinan, Shandong, China.
Abstract
BACKGROUND: Estimates of survival after curative colorectal cancer (CRC) surgery are the basis of patient care and treatment planning. A nomogram is a useful tool for individualized cancer prognosis. METHODS: A total of 2450 patients with nonmetastatic CRC were included to develop a nomogram. Prognostic factors were identified and integrated by the Cox proportional hazards model. Then, we developed and validated a prognostic nomogram. The performance of this model was assessed by the concordance index (C-index) and a calibration curve. The nomogram was internally validated by bootstrapping and externally validated with a separate database of 299 patients from The Cancer Genome Atlas. RESULTS: Age, T stage, N stage, histological type, tumor location, lymph-vascular invasion, preoperative carcinoembryonic antigen, and sample lymph nodes were integrated into the nomogram. The C-index of the nomogram for predicting overall survival was higher than that of the seventh edition American Joint Committee on Cancer TNM staging system (training data set, 0.76 vs 0.68, respectively; P < 0.001; validation data set, 0.78 vs 0.69, respectively; P = 0.003). CONCLUSION: We developed a prognostic nomogram for patients with nonmetastatic CRC, which could provide a more individualized outcome prognostication than that afforded by the TNM staging system by using common clinicopathologic factors.
BACKGROUND: Estimates of survival after curative colorectal cancer (CRC) surgery are the basis of patient care and treatment planning. A nomogram is a useful tool for individualized cancer prognosis. METHODS: A total of 2450 patients with nonmetastatic CRC were included to develop a nomogram. Prognostic factors were identified and integrated by the Cox proportional hazards model. Then, we developed and validated a prognostic nomogram. The performance of this model was assessed by the concordance index (C-index) and a calibration curve. The nomogram was internally validated by bootstrapping and externally validated with a separate database of 299 patients from The Cancer Genome Atlas. RESULTS: Age, T stage, N stage, histological type, tumor location, lymph-vascular invasion, preoperative carcinoembryonic antigen, and sample lymph nodes were integrated into the nomogram. The C-index of the nomogram for predicting overall survival was higher than that of the seventh edition American Joint Committee on Cancer TNM staging system (training data set, 0.76 vs 0.68, respectively; P < 0.001; validation data set, 0.78 vs 0.69, respectively; P = 0.003). CONCLUSION: We developed a prognostic nomogram for patients with nonmetastatic CRC, which could provide a more individualized outcome prognostication than that afforded by the TNM staging system by using common clinicopathologic factors.