Int J Biol Sci 2020; 16(7):1230-1237. doi:10.7150/ijbs.39161

Research Paper

Development and validation of a novel nomogram to predict overall survival in gastric cancer with lymph node metastasis

Minjie Mao1*, Ao Zhang2*, Yi He3*, Lin Zhang1*, Wen Liu1, Yiling Song1, Shuqi Chen4, Guanmin Jiang5✉, Xueping Wang1✉

1. Department of Laboratory Medicine, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China; Sun Yat-sen University Cancer Center, Guangzhou, China
2. State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
3. Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
4. Guangzhou Medical University, Guangzhou, China
5. Department of Clinical Laboratory, The Fifth Affiliated Hospital, Sun Yat-sen University, Zhuhai, Guangdong, China
* Minjie Mao, Ao Zhang, Yi He and Lin Zhang contributed equally to this work.

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Citation:
Mao M, Zhang A, He Y, Zhang L, Liu W, Song Y, Chen S, Jiang G, Wang X. Development and validation of a novel nomogram to predict overall survival in gastric cancer with lymph node metastasis. Int J Biol Sci 2020; 16(7):1230-1237. doi:10.7150/ijbs.39161. Available from http://www.ijbs.com/v16p1230.htm

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Abstract

Gastric cancer (GC) with lymph node metastasis (LNM) at diagnosis is associated with a unstable prognosis and indefinite survival times. The aim of the present study was to construct and validate a model for the Overall survival (OS) estimation for patients with LNM. The nomogram was constructed to predict the OS for LNM-positive GC using the primary group of 836 patients and validated using an independent cohort of 411 patients. Factors in the nomogram were identified by multivariate Cox hazard analysis. The predictive capability of nomogram was evaluated by calibration analysis and decision curve analysis. Multivariate analysis suggested that eight pre-treatment characteristics were used for developing the nomogram. In the primary cohort, the C-index for OS prediction was 0.788 (95% CI: 0.753-0.823), while in validation cohort, the C-index for OS prediction was 0.769 (95% CI: 0. 720-0.818). The calibration plot for the probability of OS and decision curve analyses showed an optimal agreement. Based on the nomogram, we could divided patients into three groups: low-risk group, middle-risk group and a high-risk group(p <0.001).Taken together, we have provided an easy-to-used and accurate tool for predicting OS, furthermore could be used for risk stratification of OS of LNM-positive GC patients.

Keywords: gastric cancer, prognosis, nomogram, lymph node metastasis