title: Risk model of in-hospital mortality after pulmonary resection for cancer: a national database of the French Society of Thoracic and Cardiovascular Surgery (Epithor).
abstract: OBJECTIVE
  The estimation of risk-adjusted in-hospital mortality is essential to allow each thoracic surgery team to be compared with national benchmarks. The objective of this study is to develop and validate a risk model of mortality after pulmonary resection.
  
  
  METHODS
  A total of 18,049 lung resections for non-small cell lung cancer were entered into the French national database Epithor. The primary outcome was in-hospital mortality. Two independent analyses were performed with comorbidity variables. The first analysis included variables as independent predictive binary comorbidities (model 1). The second analysis included the number of comorbidities per patient (model 2).
  
  
  RESULTS
  In model 1 predictors for mortality were age, sex, American Society of Anesthesiologists score, performance status, forced expiratory volume (as a percentage), body mass index (in kilograms per meter squared), side, type of lung resection,extended resection, stage, chronic bronchitis, cardiac arrhythmia, coronary artery disease, congestive heart failure, alcoholism, history of malignant disease, and prior thoracic surgery. In model 2 predictors were age, sex, American Society of Anesthesiologists score, performance status, forced expiratory volume, body mass index, side, type of lung resection, extended resection, stage, and number of comorbidities per patient. Models 1 and 2 were well calibrated, with a slope correction factor of 0.96 and of 0.972, respectively. The area under the receiver operating characteristic curve was 0.784 (95% confidence interval, 0.76-0.8) in model 1 and 0.78 (95% confidence interval, 0.76-0.797) in model 2.
  
  
  CONCLUSIONS
  Our preference is for the well-calibrated model 2 because it is easier to use in practice to estimate the adjusted postoperative mortality of lung resections for cancer.
authors.affiliation: Department of Thoracic Surgery, CHU Dijon, France. alain.bernard@chu-dijon.fr
authors.forename: Alain
authors.initials: A
authors.lastname: Bernard
authors.forename: Caroline
authors.initials: C
authors.lastname: Rivera
authors.forename: Pierre Benoit
authors.initials: PB
authors.lastname: Pages
authors.forename: Pierre Emmanuel
authors.initials: PE
authors.lastname: Falcoz
authors.forename: Eric
authors.initials: E
authors.lastname: Vicaut
authors.forename: Marcel
authors.initials: M
authors.lastname: Dahan
mesh_terms: D000368:Aged; D002289:Carcinoma, Non-Small-Cell Lung / Q000401:mortality / Q000601:surgery*; D016009:Chi-Square Distribution; D019992:Databases as Topic; D005260:Female; D005602:France / Q000453:epidemiology; D017052:Hospital Mortality; D006801:Humans; D008175:Lung Neoplasms / Q000401:mortality / Q000601:surgery*; D008297:Male; D008875:Middle Aged; D016017:Odds Ratio; D011013:Pneumonectomy / Q000401:mortality*; D012372:ROC Curve; D012044:Regression Analysis; D015203:Reproducibility of Results; D018570:Risk Assessment; D012307:Risk Factors; D012955:Societies, Medical; D016896:Treatment Outcome