title: Quantitative benefit-risk assessment using only qualitative information on utilities.
abstract: Utilities of pertinent clinical outcomes are crucial variables for assessing the benefits and risks of drugs, but numerical data on utilities may be unreliable or altogether missing. We propose a method to incorporate qualitative information into a probabilistic decision analysis framework for quantitative benefit-risk assessment.
  
  
  
  To investigate whether conclusive results can be obtained when the only source of discriminating information on utilities is widely agreed upon qualitative relations, for example, ''sepsis is worse than transient headache'' or ''alleviation of disease is better without than with complications.''
  
  
  
  We used the structure and probabilities of 3 published models that were originally evaluated based on the standard metric of quality-adjusted life years (QALYs): terfenadine versus chlorpheniramine for the treatment of allergic rhinitis, MCV4 vaccination against meningococcal disease, and alosetron for irritable bowel syndrome. For each model, we identified clinically straightforward qualitative relations among the outcomes. Using Monte Carlo simulations, the resulting utility distributions were then combined with the previously specified probabilities, and the rate of preference in terms of expected utility was determined for each alternative.
  
  
  
  Our approach conclusively favored MCV4 vaccination, and it was concordant with the QALY assessments for the MCV4 and terfenadine versus chlorpheniramine case studies. For alosetron, we found a possible unfavorable benefit-risk balance for highly risk-averse patients not identified in the original analysis.
  
  
  
  Incorporation of widely agreed upon qualitative information into quantitative benefit-risk assessment can provide for conclusive results. The methods presented should prove useful in both population and individual-level assessments, especially when numerical utility data are missing or unreliable, and constraints on time or money preclude its collection.
authors.affiliation: Uppsala Monitoring Centre, World Health Organization Collaborating Centre for International Drug Monitoring, Uppsala, Sweden (OC, GNN, IRE)|Department of Computer and Systems Sciences, Stockholm University, Stockholm, Sweden (OC, LE)
authors.forename: Ola
authors.initials: O
authors.lastname: Caster
authors.affiliation: Uppsala Monitoring Centre, World Health Organization Collaborating Centre for International Drug Monitoring, Uppsala, Sweden (OC, GNN, IRE)|Department of Mathematics, Stockholm University, Stockholm, Sweden (GNN)
authors.forename: G Niklas
authors.initials: GN
authors.lastname: Norén
authors.affiliation: Department of Computer and Systems Sciences, Stockholm University, Stockholm, Sweden (OC, LE)
authors.forename: Love
authors.initials: L
authors.lastname: Ekenberg
authors.affiliation: Uppsala Monitoring Centre, World Health Organization Collaborating Centre for International Drug Monitoring, Uppsala, Sweden (OC, GNN, IRE)
authors.forename: I Ralph
authors.initials: IR
authors.lastname: Edwards
mesh_terms: D002243:Carbolines / Q000627:therapeutic use; D002744:Chlorpheniramine / Q000627:therapeutic use; D006801:Humans; D006967:Hypersensitivity / Q000188:drug therapy; D043183:Irritable Bowel Syndrome / Q000188:drug therapy; D022401:Meningococcal Vaccines / Q000008:administration & dosage; D009010:Monte Carlo Method; D011336:Probability; D019057:Quality-Adjusted Life Years; D018570:Risk Assessment; D016593:Terfenadine / Q000627:therapeutic use
chemical_list: D002243:Carbolines; D022401:Meningococcal Vaccines; C090840:alosetron; D002744:Chlorpheniramine; D016593:Terfenadine