title: Integrating mortality and morbidity outcomes: using quality-adjusted life years in critical care trials.
abstract: BACKGROUND
  Outcome measures that integrate mortality and morbidity, like quality-adjusted life years (QALYs), have been proposed for critical care clinical trials.
  
  
  OBJECTIVE
  We sought to describe the distribution of QALYs in critically ill patients and estimate sample size requirements for a hypothetical trial using QALYs as the primary outcome.
  
  
  METHODS
  We used data from a prospective cohort study of survivors of acute respiratory distress syndrome to generate utility values and calculate QALYs at 6 and 12 months. Using multiple simulations, we estimated the required sample sizes for multiple outcome scenarios in a hypothetical trial, including a base-case wherein the intervention improved both mortality and QALYs among survivors.
  
  
  RESULTS
  From 195 enrolled patients, follow-up was sufficient to generate QALY outcomes for 168 (86.2%) at 6 months and 159 (81.5%) at 1 year. For a hypothetical intervention that reduced mortality from 48 to 44% and improved QALYs by 0.025 in survivors at 6 months, the required per-group sample size was 571 (80% power; two-sided α = 0.05), compared with 2,436 patients needed for a comparison focusing on mortality alone. When only mortality or QALY in survivors (but not both) showed improvement by these amounts, 3,426 and 1,827 patients per group were needed, respectively. When mortality and morbidity effects moved in opposite directions, simulation results became impossible to interpret.
  
  
  CONCLUSIONS
  QALYs may be a feasible outcome in critical care trials yielding a patient-centered result and major gains in statistical power under certain conditions, but this approach is susceptible to several threats, including loss to follow-up.
authors.affiliation: Interdepartmental Division of Critical Care Medicine, The University of Toronto, Toronto, Ontario, Canada.
authors.forename: Niall D
authors.initials: ND
authors.lastname: Ferguson
authors.forename: Damon C
authors.initials: DC
authors.lastname: Scales
authors.forename: Ruxandra
authors.initials: R
authors.lastname: Pinto
authors.forename: M Elizabeth
authors.initials: ME
authors.lastname: Wilcox
authors.forename: Deborah J
authors.initials: DJ
authors.lastname: Cook
authors.forename: Gordon H
authors.initials: GH
authors.lastname: Guyatt
authors.forename: Holger J
authors.initials: HJ
authors.lastname: Schünemann
authors.forename: John C
authors.initials: JC
authors.lastname: Marshall
authors.forename: Margaret S
authors.initials: MS
authors.lastname: Herridge
authors.forename: Maureen O
authors.initials: MO
authors.lastname: Meade
mesh_terms: D002986:Clinical Trials as Topic / Q000379:methods*; D015331:Cohort Studies; D003422:Critical Care; D016638:Critical Illness; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D008297:Male; D008875:Middle Aged; D017063:Outcome Assessment, Health Care / Q000379:methods* / Q000706:statistics & numerical data; D011446:Prospective Studies; D019057:Quality-Adjusted Life Years; D012128:Respiratory Distress Syndrome / Q000401:mortality*; D018401:Sample Size; D016019:Survival Analysis