title: Classification based on the combination of molecular and pathologic predictors is superior to molecular classification on prognosis in colorectal carcinoma.
abstract: OBJECTIVE
  Classification based on a combination of molecular and pathologic predictors had never been done using hierarchical cluster analysis. For this purpose, we identified prognostic classification based on molecular predictors, pathologic and molecular predictors, and compared their respective prognostic efficacy together with that of tumor-node-metastasis (TNM) stage. Moreover, we investigated the prognostic significance of molecular classification in different TNM stage.
  
  
  METHODS
  Six pathologic predictors (p) and 13 immunohistochemical predictors (m) were investigated in 221 colorectal carcinomas. Unsupervised hierarchical clustering analysis was done to group the data. Survival analysis was done by Kaplan-Meier method and log-rank test, and by multivariate COX proportional hazard model.
  
  
  RESULTS
  Six pathologic predictors and four molecular predictors were of significant prognostic value (P <or= 0.05). One molecular predictor showed a trend toward significance (P = 0.085). Hierarchical clustering analysis was done based on different combinations (5p, 13m, 5m, 5p13m, and 5p5m), and distinct groups were produced except 5p (the TNM stage was excluded). Groups identified by 5m (P = 0.053) and 5p5m (P = 0.000) showed significant differences in prognosis. Groups identified by 5p5m and TNM stage were confirmed as the independent prognostic factors in a multivariate COX proportional hazard model. Moreover, groups identified by 5m could predict different prognoses in patients with stage II disease.
  
  
  CONCLUSIONS
  Classification based on pathologic and immunohistochemical predictors is superior to that based only on molecular predictors on prognosis. Classification based on 5m could identify additional different prognoses in patients with stage II disease.
authors.affiliation: Department of Pathology, School of Medicine, Zhejiang University, Hangzhou, China.
authors.forename: Fangying
authors.initials: F
authors.lastname: Xu
authors.forename: Fenjuan
authors.initials: F
authors.lastname: Wang
authors.forename: Meijuan
authors.initials: M
authors.lastname: Di
authors.forename: Qiong
authors.initials: Q
authors.lastname: Huang
authors.forename: Min
authors.initials: M
authors.lastname: Wang
authors.forename: Hu
authors.initials: H
authors.lastname: Hu
authors.forename: Yisen
authors.initials: Y
authors.lastname: Jin
authors.forename: Jiankang
authors.initials: J
authors.lastname: Dong
authors.forename: Maode
authors.initials: M
authors.lastname: Lai
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D016000:Cluster Analysis; D015179:Colorectal Neoplasms / Q000145:classification* / Q000235:genetics / Q000401:mortality / Q000473:pathology; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D011379:Prognosis; D016016:Proportional Hazards Models; D019718:Receptors, CXCR4 / Q000032:analysis