title: Predicting survival in terminal cancer patients: clinical observation or quality-of-life evaluation?
abstract: BACKGROUND
  This study compares the relative prognostic power of clinical variables and quality-of-life (QoL) measures in a population of terminal cancer patients.
  
  
  METHODS
  A prospective cohort study in 58 Italian Palliative Care Units. Of the 601 randomly selected terminal cancer patients, 574 were followed until death in order to compare clinical and QoL variables (using the Therapy Impact Questionnaire (TIQ) as predictors of survival, and assess whether their combined implementation makes prediction more accurate.
  
  
  RESULTS
  The clinical variables most strongly associated with survival were dyspnoea, cachexia, Katz's ADL, oliguria, dysphagia, dehydration, liver and acute kidney failure and delirium (hazard ratios (HR) ranging from 2.10 to 3.01). Only the first four kept their strength once introduced in the Cox model (HRs ranging from 1.95 to 2.22). In the TIQ primary scale the strongest predictors were physical wellbeing, fatigue, functional status and cognitive status (HRs ranging from 1.42 to 1.71), but only fatigue showed an independent prognostic relevance (90% of selection). In the TIQ global scales, the Physical Symptom Index showed a stronger association with survival (HR 1.71) than the Therapy Impact Index (HR 1.47). The former marginally improved the prognostic power of the model when added to clinical variables. Internal validation confirmed that the results were not spurious.
  
  
  CONCLUSIONS
  In terminal cancer patients, clinical variables are better predictors of survival than QoL. The large residual variability not accounted for by the model (approximately 70%) suggests that survival is also influenced by factors unlikely to be identified in a survey.
authors.affiliation: Istituto de Ricerca in Medicina Palliativa 'L Maestroni, Cremona. toscani.f@dinet.it
authors.forename: Pietro
authors.initials: P
authors.lastname: Toscani
authors.forename: Cinzia
authors.initials: C
authors.lastname: Brunelli
authors.forename: Guido
authors.initials: G
authors.lastname: Miccinesi
authors.forename: Massimo
authors.initials: M
authors.lastname: Costantini
authors.forename: Michele
authors.initials: M
authors.lastname: Gallucci
authors.forename: Marcello
authors.initials: M
authors.lastname: Tamburini
authors.forename: Eugenio
authors.initials: E
authors.lastname: Paci
authors.forename: Paolo
authors.initials: P
authors.lastname: Di Giulio
authors.forename: Carlo
authors.initials: C
authors.lastname: Peruselli
mesh_terms: D000368:Aged; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D009369:Neoplasms / Q000401:mortality*; D011379:Prognosis; D011788:Quality of Life; D016019:Survival Analysis; D019452:Terminally Ill / Q000706:statistics & numerical data*