title: A novel staging model to classify oesophageal squamous cell carcinoma patients in China.
abstract: BACKGROUND
  Oesophageal squamous cell carcinoma (ESCC) is the predominant subtype of oesophageal carcinoma in China, with the overall 5-year survival rate of <10%. The current tumour-node-metastasis (TNM) staging system has become so complex that it is not easy to use in the life expectancy assessment. We aim to combine clinical variables and biomarkers to develop and validate a relative simple and reliable model, named the FENSAM, for ESCC prognosis.
  
  
  METHODS
  To build the FENSAM, we analysed 22 potential prognostic factors from 461 patients, including 9 biomarkers (Ezrin, Fascin, desmocollin 2 (DSC2), pFascin, activating transcription factor 3 (ATF3), connective-tissue growth factor (CTGF), neutrophil gelatinase-associated lipocalin (NGAL), NGAL receptor (NGALR), and cysteine-rich angiogenic protein 61 (CYR61)) and other 13 clinical variables. We selected significant factors associated with survival of ESCC patients, and used them to build our FENSAM model. We then obtained the hazard risk score of the model to classify ESCC patients. In addition, we validated the model in an independent cohort of 290 patients from the same hospital. The predictive performance of the model was assessed by the Area under the Receiver Operating Characteristic Curve (AUC) and Kaplan-Meier survival analysis.
  
  
  RESULTS
  We found six markers significantly associated with survival of ESCC patients (Ezrin, Fascin, ATF3, surgery extent, N-stage, and M-stage). They were combined to create a novel four-stage FENSAM model for patients' classification. FENSAM possessed a high classification precision similar to the TNM staging system, but with a much simpler model. The efficiency of FENSAM was evaluated by different quantiles of AUC and the results of survival analysis. The validation result demonstrated the potential of the FENSAM model to improve classification accuracy for ESCC patients.
  
  
  CONCLUSIONS
  FENSAM provides an alternative classifier for ESCC patients with a high classification precision using a simple model.
authors.affiliation: 1] Department of Biomedical Engineering, Zhongshan School of Medicine, Sun Yat-Sen University, 135 Xin Gang W. Road, Guangzhou, China [2] The Key Laboratory of Molecular Biology for High Cancer Incidence Coastal Chaoshan Area, Shantou University Medical College, Shantou, China [3] Southern China Research Center of Statistical Science, Sun Yat-Sen University, Guangzhou 510275, China.
authors.forename: H
authors.initials: H
authors.lastname: Tan
authors.affiliation: 1] Southern China Research Center of Statistical Science, Sun Yat-Sen University, Guangzhou 510275, China [2] Yale University School of Public Health, New Haven, CT, USA [3] Department of Statistical Science, School of Mathematics and Computational Science, Sun Yat-Sen University, Guangzhou, China.
authors.forename: H
authors.initials: H
authors.lastname: Zhang
authors.affiliation: The Key Laboratory of Molecular Biology for High Cancer Incidence Coastal Chaoshan Area, Shantou University Medical College, Shantou, China.
authors.forename: J
authors.initials: J
authors.lastname: Xie
authors.affiliation: The Key Laboratory of Molecular Biology for High Cancer Incidence Coastal Chaoshan Area, Shantou University Medical College, Shantou, China.
authors.forename: B
authors.initials: B
authors.lastname: Chen
authors.affiliation: 1] Southern China Research Center of Statistical Science, Sun Yat-Sen University, Guangzhou 510275, China [2] Department of Statistical Science, School of Mathematics and Computational Science, Sun Yat-Sen University, Guangzhou, China.
authors.forename: C
authors.initials: C
authors.lastname: Wen
authors.affiliation: 1] Southern China Research Center of Statistical Science, Sun Yat-Sen University, Guangzhou 510275, China [2] Department of Statistical Science, School of Mathematics and Computational Science, Sun Yat-Sen University, Guangzhou, China.
authors.forename: X
authors.initials: X
authors.lastname: Guo
authors.affiliation: Department of Pathology, Shantou Central Hospital, Affiliated Shantou Hospital of Sun Yat-Sen University, Shantou, China.
authors.forename: Q
authors.initials: Q
authors.lastname: Zhao
authors.affiliation: Department of Pathology, Shantou Central Hospital, Affiliated Shantou Hospital of Sun Yat-Sen University, Shantou, China.
authors.forename: Z
authors.initials: Z
authors.lastname: Wu
authors.affiliation: Department of Pathology, Shantou Central Hospital, Affiliated Shantou Hospital of Sun Yat-Sen University, Shantou, China.
authors.forename: J
authors.initials: J
authors.lastname: Shen
authors.affiliation: The Key Laboratory of Molecular Biology for High Cancer Incidence Coastal Chaoshan Area, Shantou University Medical College, Shantou, China.
authors.forename: J
authors.initials: J
authors.lastname: Wu
authors.affiliation: The Key Laboratory of Molecular Biology for High Cancer Incidence Coastal Chaoshan Area, Shantou University Medical College, Shantou, China.
authors.forename: X
authors.initials: X
authors.lastname: Xu
authors.affiliation: The Key Laboratory of Molecular Biology for High Cancer Incidence Coastal Chaoshan Area, Shantou University Medical College, Shantou, China.
authors.forename: E
authors.initials: E
authors.lastname: Li
authors.affiliation: The Key Laboratory of Molecular Biology for High Cancer Incidence Coastal Chaoshan Area, Shantou University Medical College, Shantou, China.
authors.forename: L
authors.initials: L
authors.lastname: Xu
authors.affiliation: 1] Department of Biomedical Engineering, Zhongshan School of Medicine, Sun Yat-Sen University, 135 Xin Gang W. Road, Guangzhou, China [2] Southern China Research Center of Statistical Science, Sun Yat-Sen University, Guangzhou 510275, China [3] Department of Statistical Science, School of Mathematics and Computational Science, Sun Yat-Sen University, Guangzhou, China.
authors.forename: X
authors.initials: X
authors.lastname: Wang
mesh_terms: D000368:Aged; D014408:Biomarkers, Tumor / Q000097:blood; D002294:Carcinoma, Squamous Cell / Q000097:blood / Q000235:genetics* / Q000473:pathology*; D002352:Carrier Proteins / Q000097:blood; D002681:China; D003598:Cytoskeletal Proteins / Q000097:blood; D004938:Esophageal Neoplasms / Q000097:blood / Q000235:genetics / Q000473:pathology*; D005260:Female; D006801:Humans; D053208:Kaplan-Meier Estimate; D008207:Lymphatic Metastasis; D008297:Male; D008840:Microfilament Proteins / Q000097:blood; D008875:Middle Aged; D011379:Prognosis; D000099149:Ezrin
chemical_list: D014408:Biomarkers, Tumor; D002352:Carrier Proteins; D003598:Cytoskeletal Proteins; D008840:Microfilament Proteins; D000099149:Ezrin; C020324:fascin