title: Quantitative contribution of prognosticators to oncologic outcome after rectal cancer resection.
abstract: BACKGROUND
  Prognostication is an important aspect of medical practice. It relies on statistical modeling testing the correlation of variables with the outcome of interest.
  
  
  OBJECTIVE
  In contrast with the classic approach of predictive modeling, this study aimed to estimate the unique, individual, and relative contributions. This includes the quantitative contributions of patient-, tumor-, and treatment-related factors to oncologic outcome after rectal cancer resection.
  
  
  METHODS
  This was a retrospective analysis of prospectively registered data.
  
  
  METHODS
  The study included 65 hospitals participating on a voluntary basis in the Project on Cancer of the Rectum, a Belgian multidisciplinary improvement project of rectal cancer care.
  
  
  METHODS
  A total of 1470 patients presenting midrectal or low-rectal adenocarcinoma without distant metastasis were included.
  
  
  METHODS
  The study intervention was total mesorectal excision with or without sphincter preservation.
  
  
  METHODS
  The unique, individual, and relative contributions of a set of covariables to the statistical variability of the distant metastasis rate and overall survival have been calculated.
  
  
  RESULTS
  The 5-year distant metastasis rate was 21% and overall survival 76%. A large amount of the variability of the outcomes (ie, 83.6% to 84.2%) could not be predicted by the prognostic factors. Unique contributions of the predictors ranged from 0.1% to 3.1%. The 3 risk factors with the highest unique contribution for distant metastasis were lymph node ratio, pathologic tumor stage, and total mesorectal quality; for overall survival they were age, lymph node ratio, and ASA score.
  
  
  CONCLUSIONS
  The main weakness of this study was incomplete participation and registration in the Project on Cancer of the Rectum.
  
  
  CONCLUSIONS
  Several factors influence oncologic outcomes and are present in prediction models. However, the models predict relatively little of outcome variation.
authors.affiliation: 1 Colorectal Surgery Unit, Cliniques Universitaires Saint-Luc, Brussels, Belgium 2 Department of Abdominal Surgery, University Clinic Gasthuisberg, Leuven, Belgium 3 I-Biostat, Katholieke Universiteit Leuven, Leuven, Belgium 4 I-Biostat, Universiteit Hasselt, Hasselt, Belgium.
authors.forename: Daniel
authors.initials: D
authors.lastname: Leonard
authors.forename: Freddy
authors.initials: F
authors.lastname: Penninckx
authors.forename: Annouschka
authors.initials: A
authors.lastname: Laenen
authors.forename: Alex
authors.initials: A
authors.lastname: Kartheuser
mesh_terms: D000230:Adenocarcinoma / Q000401:mortality / Q000473:pathology / Q000556:secondary / Q000601:surgery*; D000368:Aged; D005260:Female; D006801:Humans; D008207:Lymphatic Metastasis; D008297:Male; D008875:Middle Aged; D009364:Neoplasm Recurrence, Local; D009367:Neoplasm Staging; D011379:Prognosis; D012004:Rectal Neoplasms / Q000401:mortality / Q000473:pathology / Q000601:surgery*; D012189:Retrospective Studies; D015996:Survival Rate; D016896:Treatment Outcome