Clinical Research Papers:
A new predictive model combined of tumor size, lymph nodes count and lymphovascular invasion for survival prognosis in patients with lymph node-negative gastric cancer
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Lin-Yong Zhao1,2,3,*, Xiao-Long Chen1,2,*, Yi-Gao Wang1,2,3,*, Yue Xin3, Wei-Han Zhang1,2,3, Yin-Su Wang3, Xin-Zu Chen1,2, Kun Yang1,2, Kai Liu1,2, Lian Xue1,2,3, Bo Zhang1, Zhi-Xin Chen1, Jia-Ping Chen1, Zong-Guang Zhou1 and Jian-Kun Hu1,2
1 Department of Gastrointestinal Surgery, West China Hospital, Sichuan University, Chengdu, China
2 Laboratory of Gastric Cancer, State Key Laboratory of Biotherapy/Collaborative Innovation Center of Biotherapy, West China Hospital, Sichuan University, Chengdu, China
3 West China School of Medicine, Sichuan University, Chengdu, China
* These authors have contributed equally to this work
Jian-Kun Hu, email:
Keywords: predictive model; gastric cancer; tumor size; lymphovascular invasion; lymph nodes count
Received: February 15, 2016 Accepted: July 18, 2016 Published: August 04, 2016
Background: Various factors may affect the clinical prognosis of lymph node-negative gastric cancer (GC) patients. This study aimed to provide evaluable prognostic information of combination of tumor size (Ts), lymph nodes count (LNs) and lymphovascular invasion (LVI) in lymph node-negative GC patients.
Methods: A total of 1,019 node-negative GC patients were enrolled in this retrospective study from 2000 to 2010. The cutoff points of Ts and LNs were determined using X-tile and patients were randomly categorized into training and validation sets by the sample size ratio 1:1. The clinicopathologic characteristics were analyzed and survival prognostic factors were identified, whereas the survival prediction accuracy was also compared by C-index during the different independent prognostic factors.
Results: The cutoff points for Ts were 3cm and 5cm, while 14 was the cutoff point for LNs. Age, T stage, Ts, LNs and LVI were identified as independent prognostic factors in node-negative GC patients, and a new prognostic predictive model, TsNL staging system which was composed of Ts, LNs and LVI, was proposed in this study. Compared with T staging system, significant improvement of predictive accuracy for TsNL system was found. Furthermore, nomogram based on TsNL was more accurate in prognostic prediction than that based on Ts, LNs and LVI, separately.
Conclusions: Age, T stage, Ts, LNs and LVI were independent prognostic factors in lymph node-negative GC patients. The TsNL staging system, composed of Ts, LNs and LVI, which was closely associated with clinicopathologic features, may improve the prognostic prediction accuracy in node-negative GC patients.
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