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Development and validation of a nomogram for predicting survival in Chinese han patients with resected colorectal cancer
Author(s) -
Li Jiqing,
Gu Jianhua,
Ma Xiaotian,
Li Xiao,
Liu Xiaojuan,
Kang Fengling,
Xue Fuzhong
Publication year - 2018
Publication title -
journal of surgical oncology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.201
H-Index - 111
eISSN - 1096-9098
pISSN - 0022-4790
DOI - 10.1002/jso.25213
Subject(s) - nomogram , medicine , colorectal cancer , proportional hazards model , tnm staging system , oncology , stage (stratigraphy) , carcinoembryonic antigen , concordance , colectomy , t stage , cancer , overall survival , staging system , paleontology , biology
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.