title: Prognostic factors for survival in advanced non-small-cell lung cancer: univariate and multivariate analyses including recursive partitioning and amalgamation algorithms in 1,052 patients. The European Lung Cancer Working Party.
abstract: OBJECTIVE
  This study attempted to determine the prognostic value for survival of various pretreatment characteristics in patients with nonresectable non-small-cell lung cancer in the context of more than 10 years of experience of a European Cooperative Group.
  
  
  METHODS
  We included in the analysis all eligible patients (N = 1,052) with advanced non-small-cell lung cancer registered onto one of seven trials conducted by the European Lung Cancer Working Party (ELCWP) during one decade. The patients were treated by chemotherapy regimens based on platinum derivatives. We prospectively collected 23 variables and analyzed them by univariate and multivariate methods.
  
  
  RESULTS
  The global estimated median survival time was 29 weeks, with a 95% confidence interval of 27 to 30 weeks. After univariate analysis, we applied two multivariate statistical techniques. In a Cox regression model, the selected explanatory variables were disease extent, Karnofsky performance status, WBC and neutrophil counts, metastatic involvement of skin, serum calcium level, age, and sex. These results were confirmed by application of recursive partitioning and amalgamation algorithms (RECPAM), which led to classification of the patients into four homogeneous subgroups.
  
  
  CONCLUSIONS
  We confirmed by our analysis the role of well-known independent prognostic factors for survival, but also identified the effect of the neutrophil count, rarely studied, with the use of two methods: a classical Cox regression model and a RECPAM analysis. The classification of patients into the four subgroups we obtained needs to be validated in other series.
authors.affiliation: Unité de Biostatistique, Institut Jules Bordet, Bruxelles, Belgium.
authors.forename: M
authors.initials: M
authors.lastname: Paesmans
authors.forename: J P
authors.initials: JP
authors.lastname: Sculier
authors.forename: P
authors.initials: P
authors.lastname: Libert
authors.forename: G
authors.initials: G
authors.lastname: Bureau
authors.forename: G
authors.initials: G
authors.lastname: Dabouis
authors.forename: J
authors.initials: J
authors.lastname: Thiriaux
authors.forename: J
authors.initials: J
authors.lastname: Michel
authors.forename: O
authors.initials: O
authors.lastname: Van Cutsem
authors.forename: R
authors.initials: R
authors.lastname: Sergysels
authors.forename: P
authors.initials: P
authors.lastname: Mommen
mesh_terms: D000465:Algorithms; D000704:Analysis of Variance; D000970:Antineoplastic Agents / Q000627:therapeutic use; D014408:Biomarkers, Tumor / Q000032:analysis; D001772:Blood Cell Count; D002289:Carcinoma, Non-Small-Cell Lung / Q000188:drug therapy / Q000401:mortality* / Q000503:physiopathology / Q000556:secondary; D005260:Female; D006801:Humans; D017567:Karnofsky Performance Status; D008175:Lung Neoplasms / Q000188:drug therapy / Q000401:mortality* / Q000503:physiopathology; D008297:Male; D008875:Middle Aged; D011379:Prognosis; D016016:Proportional Hazards Models; D012189:Retrospective Studies; D016019:Survival Analysis; D015431:Weight Loss
chemical_list: D000970:Antineoplastic Agents; D014408:Biomarkers, Tumor