title: Classification of gastric carcinoma using the Goseki system provides prognostic information additional to TNM staging.
abstract: BACKGROUND
  Due to the high variability of the epidemiology, genetics, morphology, and biologic behavior of gastric carcinoma, many classification systems are in use, e.g., the World Health Organization (WHO) classification; tumor differentiation; the criteria of Ming, Mulligan, and Laurén; and the recently introduced Goseki classification. In the authors' opinion, the TNM staging is the most valuable classification system, with a prognostic value for survival.
  
  
  METHODS
  To assess the reproducibility and usefulness of these systems in clinical practice, material from 285 gastric carcinoma patients entered in the Dutch Gastric Cancer Trial was analyzed by a panel of 5 experienced gastrointestinal pathologists. The presence of eosinophilic and lymphocytic infiltrates was analyzed in addition to the TNM staging.
  
  
  RESULTS
  Of the analyzed classification systems, only TNM stage, tumor differentiation, eosinophilic infiltrate, and the Goseki system contained information associated with the survival of patients with gastric carcinoma. The reproducibility was perfect for tumor differentiation (Kappa 1.00), nearly perfect for the WHO and Goseki classifications (Kappa 0.86 and 0.87, respectively), reasonably good for Laurén and lymphocytic infiltrate (Kappa 0.70), and reasonably good for eosinophilic infiltrate (Kappa 0.42).
  
  
  CONCLUSIONS
  Of all these systems, the Goseki classification was the only system with prognostic value that is additional to TNM staging.
mesh_terms: D000230:Adenocarcinoma / Q000145:classification* / Q000473:pathology; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D009361:Neoplasm Invasiveness; D009367:Neoplasm Staging / Q000379:methods*; D011379:Prognosis; D015203:Reproducibility of Results; D013274:Stomach Neoplasms / Q000145:classification* / Q000473:pathology; D016019:Survival Analysis