title: A scoring system based on artificial neural network for predicting 10-year survival in stage II A colon cancer patients after radical surgery.
abstract: Nearly 20% patients with stage II A colon cancer will develop recurrent disease post-operatively. The present study aims to develop a scoring system based on Artificial Neural Network (ANN) model for predicting 10-year survival outcome. The clinical and molecular data of 117 stage II A colon cancer patients from Sun Yat-sen University Cancer Center were used for training set and test set; poor pathological grading (score 49), reduced expression of TGFBR2 (score 33), over-expression of TGF-β (score 45), MAPK (score 32), pin1 (score 100), β-catenin in tumor tissue (score 50) and reduced expression of TGF-β in normal mucosa (score 22) were selected as the prognostic risk predictors. According to the developed scoring system, the patients were divided into 3 subgroups, which were supposed with higher, moderate and lower risk levels. As a result, for the 3 subgroups, the 10-year overall survival (OS) rates were 16.7%, 62.9% and 100% (P < 0.001); and the 10-year disease free survival (DFS) rates were 16.7%, 61.8% and 98.8% (P < 0.001) respectively. It showed that this scoring system for stage II A colon cancer could help to predict long-term survival and screen out high-risk individuals for more vigorous treatment.
authors.affiliation: Department of Colorectal Surgery, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine Guangzhou, P.R. China.
authors.forename: Jian-Hong
authors.initials: JH
authors.lastname: Peng
authors.affiliation: Department of Colorectal Surgery, Department of Experimental Research, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine Guangzhou, P. R. China.
authors.forename: Yu-Jing
authors.initials: YJ
authors.lastname: Fang
authors.affiliation: School of Mathematics and Computational Science,Sun Yat-sen University, Guangzhou, P.R. China,.|Guangdong Provincial Key Laboratory of Computational Science, Sun Yat-sen University, Guangzhou, P.R. China.
authors.forename: Cai-Xia
authors.initials: CX
authors.lastname: Li
authors.affiliation: Department of Colorectal Surgery, Department of Experimental Research, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine Guangzhou, P. R. China.
authors.forename: Qing-Jian
authors.initials: QJ
authors.lastname: Ou
authors.affiliation: Department of Colorectal Surgery, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine Guangzhou, P.R. China.
authors.forename: Wu
authors.initials: W
authors.lastname: Jiang
authors.affiliation: Department of pathology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine Guangzhou, P. R. China.
authors.forename: Shi-Xun
authors.initials: SX
authors.lastname: Lu
authors.affiliation: Department of Colorectal Surgery, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine Guangzhou, P.R. China.
authors.forename: Zhen-Hai
authors.initials: ZH
authors.lastname: Lu
authors.affiliation: School of Mathematics and Computational Science,Sun Yat-sen University, Guangzhou, P.R. China,.|Guangdong Provincial Key Laboratory of Computational Science, Sun Yat-sen University, Guangzhou, P.R. China.
authors.forename: Pei-Xing
authors.initials: PX
authors.lastname: Li
authors.affiliation: Department of pathology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine Guangzhou, P. R. China.
authors.forename: Jing-Ping
authors.initials: JP
authors.lastname: Yun
authors.affiliation: Department of Colorectal Surgery, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine Guangzhou, P.R. China.
authors.forename: Rong-Xin
authors.initials: RX
authors.lastname: Zhang
authors.affiliation: Department of Colorectal Surgery, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine Guangzhou, P.R. China.
authors.forename: Zhi-Zhong
authors.initials: ZZ
authors.lastname: Pan
authors.affiliation: Department of Colorectal Surgery, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine Guangzhou, P.R. China.
authors.forename: De Sen
authors.initials: de S
authors.lastname: Wan
mesh_terms: D000328:Adult; D000368:Aged; D019540:Area Under Curve; D014408:Biomarkers, Tumor / Q000032:analysis; D003110:Colonic Neoplasms / Q000401:mortality* / Q000473:pathology* / Q000601:surgery; D018572:Disease-Free Survival; D005260:Female; D006801:Humans; D053208:Kaplan-Meier Estimate; D008297:Male; D008875:Middle Aged; D009364:Neoplasm Recurrence, Local / Q000401:mortality; D016571:Neural Networks, Computer; D012372:ROC Curve; D012307:Risk Factors
chemical_list: D014408:Biomarkers, Tumor
keywords: artificial neural network; colon cancer; scoring system; stage IIA; survival