title: Comparison of health state utilities using community and patient preference weights derived from a survey of patients with HIV/AIDS.
abstract: OBJECTIVE
  The authors compare health state utilities derived from a national survey of patients with HIV/AIDS to represent community-based preferences with utilities derived from the same survey representing patient preferences; explore the relationships between these utilities and the dimensions of the SF-6D health state classification; and examine the implications of differences in the source of utilities for a cost-effectiveness analysis of early treatment of patients with HIV/AIDS.
  
  
  METHODS
  The authors derived community-based standard gamble (SG) utilities using an algorithm developed for the SF-6D health state classification system. The authors derived patient SG utilities from HIV/AIDS patient rating scale self-assessments using a power transformation. Data were from the HIV Cost and Services Utilization Study, a probability sample of 2864 HIV-infected adults receiving care in the United States in 1996.
  
  
  RESULTS
  Patient SG utilities were higher than community SG utilities by 4% to 9% (0.979 vs. 0.937, 0.910 vs. 0.841, and 0.845 vs. 0.778; P < 0.001 for all comparisons). In regression analyses, patient SG utilities were less influenced by physical functioning, pain, and mental health dimensions of the SF-6D. The base case results of a cost-effectiveness analysis comparing early antiretroviral therapy to deferred therapy were unaffected by the choice between community ($20,100 per quality-adjusted life year) and patient ($18,400 per quality-adjusted life year) perspectives. The impact of the choice of utilities remained small in sensitivity analyses that varied the influence of treatment side effects on utilities and the initial symptom status of patients.
  
  
  CONCLUSIONS
  There are differences between community and patient utilities for HIV/AIDS health states, although even when treatment side effects are important, these differences may not affect cost-effectiveness ratios.
authors.affiliation: Center for Risk Analysis, Department of Health Policy and Management, Harvard School of Public Health, Boston, Massachusetts, USA. brs2006@med.cornell.edu
authors.forename: Bruce R
authors.initials: BR
authors.lastname: Schackman
authors.forename: Sue J
authors.initials: SJ
authors.lastname: Goldie
authors.forename: Kenneth A
authors.initials: KA
authors.lastname: Freedberg
authors.forename: Elena
authors.initials: E
authors.lastname: Losina
authors.forename: John
authors.initials: J
authors.lastname: Brazier
authors.forename: Milton C
authors.initials: MC
authors.lastname: Weinstein
mesh_terms: D000163:Acquired Immunodeficiency Syndrome / Q000188:drug therapy / Q000191:economics / Q000503:physiopathology / Q000523:psychology; D000328:Adult; D000465:Algorithms; D023241:Antiretroviral Therapy, Highly Active / Q000706:statistics & numerical data; D018791:CD4 Lymphocyte Count; D003198:Computer Simulation; D003258:Consumer Behavior / Q000191:economics / Q000706:statistics & numerical data*; D017281:Cost of Illness; D003362:Cost-Benefit Analysis; D003657:Decision Making; D015658:HIV Infections / Q000188:drug therapy / Q000191:economics / Q000503:physiopathology / Q000523:psychology*; D006305:Health Status Indicators; D006801:Humans; D007407:Interviews as Topic; D010342:Patient Acceptance of Health Care / Q000523:psychology*; D019057:Quality-Adjusted Life Years; D012044:Regression Analysis; D020377:Self Efficacy; D014481:United States