title: A Novel Prediction Model of Prognosis After Gastrectomy for Gastric Carcinoma: Development and Validation Using Asian Databases.
abstract: The prognoses of gastric cancer patients vary greatly among countries. Meanwhile, tumor-node-metastasis (TNM) staging system shows limited accuracy in predicting patient-specific survival for gastric cancer. The objective of this study was to create a simple, yet universally applicable survival prediction model for surgically treated gastric cancer patients.
  
  
  
  A prediction model of 5-year overall survival for surgically treated gastric cancer patients regardless of curability was developed using a test data set of 11,851 consecutive patients.
  
  
  
  The model's coefficients were selected based on univariate and multivariate analysis of patient, tumor, and surgical factors shown to significantly impact survival using a Cox proportional hazards model. For internal validation, discrimination was calculated with the concordance index (C-statistic) using the bootstrap method and calibration assessed. The model was externally validated using 4 data sets from 3 countries.
  
  
  
  Our model's C-statistic (0.824) showed better discrimination power than current tumor-node-metastasis staging (0.788) (P < 0.0001). Bootstrap internal validation demonstrated that coefficients remained largely unchanged between iterations, with an average C-statistic of 0.822. The model calibration was accurate in predicting 5-year survival. In the external validation, C-statistics showed good discrimination (range: 0.798-0.868) in patient data sets from 4 participating institutions in 3 different countries.
  
  
  
  Utilizing clinically practical patient, tumor, and surgical information, we developed a universally applicable prediction model for accurately determining the 5-year overall survival of gastric cancer patients after gastrectomy. Our predictive model was also valid in patients who underwent noncurative resection or inadequate lymphadenectomy.
authors.affiliation: *Department of Surgery, Columbia University College of Physicians and Surgeons, New York, NY†Department of Surgery, Eulji University School of Medicine, Seoul, Republic of Korea‡Department of Biostatistics, Yonsei University College of Medicine, Seoul, Republic of Korea§Department of Surgical Oncology, Gifu University School of Medicine, Gifu, Japan¶Department of General Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, China||Department of Surgery, Soonchunhyang University, Bucheon, Republic of Korea**Department of Surgery, Yonsei University College of Medicine, Seoul, Republic of Korea††Gastric Cancer Center, Yonsei Cancer Hospital, Yonsei University Health System, Seoul, Republic of Korea‡‡Robot and MIS Center, Severance Hospital, Yonsei University Health System, Seoul, Republic of Korea.
authors.forename: Yanghee
authors.initials: Y
authors.lastname: Woo
authors.forename: Taeil
authors.initials: T
authors.lastname: Son
authors.forename: Kijun
authors.initials: K
authors.lastname: Song
authors.forename: Naoki
authors.initials: N
authors.lastname: Okumura
authors.forename: Yanfeng
authors.initials: Y
authors.lastname: Hu
authors.forename: Gyu-Seok
authors.initials: GS
authors.lastname: Cho
authors.forename: Jong Won
authors.initials: JW
authors.lastname: Kim
authors.forename: Seung-Ho
authors.initials: SH
authors.lastname: Choi
authors.forename: Sung Hoon
authors.initials: SH
authors.lastname: Noh
authors.forename: Woo Jin
authors.initials: WJ
authors.lastname: Hyung
mesh_terms: D000230:Adenocarcinoma / Q000401:mortality / Q000473:pathology* / Q000601:surgery*; D005260:Female; D005743:Gastrectomy / Q000379:methods; D006801:Humans; D053208:Kaplan-Meier Estimate; D008197:Lymph Node Excision; D008297:Male; D008875:Middle Aged; D009367:Neoplasm Staging; D011379:Prognosis; D011446:Prospective Studies; D013274:Stomach Neoplasms / Q000401:mortality / Q000473:pathology* / Q000601:surgery*; D016896:Treatment Outcome