title: Do economic evaluations of targeted therapy provide support for decision makers?
abstract: OBJECTIVE
  Decision makers must make decisions without complete information. That uncertainty can be decreased when economic evaluations use local data and can be quantified by considering the variability of all model inputs concurrently per international evaluation guidelines. It is unclear how these recommendations have been implemented in evaluations of targeted cancer therapy. By using economic evaluations of adjuvant trastuzumab, we have assessed the extent to which decision support recommendations were adopted.
  
  
  METHODS
  Systematic review.
  
  
  METHODS
  Published economic evaluations of adjuvant trastuzumab treatment in early-stage breast cancer were examined as an established example of targeted therapy. Canadian, United Kingdom, and US economic evaluation guidelines were reviewed to establish extraction criteria. Extraction characterized the use of effectiveness evidence and local data sources for model parameters, sensitivity analysis methods (scenario, univariate, multivariate, and probabilistic), and uncertainty representation (ie, cost-effectiveness plane, scatterplot, confidence ellipses, tornado diagrams, cost-effectiveness acceptability curve).
  
  
  RESULTS
  Fifteen economic evaluations of adjuvant trastuzumab were identified in the literature. Local data were used to estimate costs (15 of 15) and utilities rarely (2 of 15) but not trastuzumab efficacy. Univariate sensitivity analysis was most common (12 of 15), whereas probabilistic analysis was less frequent (10 of 15). Two-thirds of all studies provided visual representation of results and decision uncertainty.
  
  
  CONCLUSIONS
  Authors of adjuvant trastuzumab economic evaluations rarely use local data beyond costs. Quantification of uncertainty and its representation also fell short of guideline recommendations. This review demonstrates that economic evaluations of adjuvant trastuzumab, as an example of targeted cancer therapy, can be improved for decision-making support.
authors.affiliation: Faculty of Medicine, University of Calgary, Health Research Innovation Centre, 3280 Hospital Dr NW, Room 3C56, Calgary, AB T2N 4Z6.
authors.forename: Ilia L
authors.initials: IL
authors.lastname: Ferrusi
authors.forename: Natasha B
authors.initials: NB
authors.lastname: Leighl
authors.forename: Nathalie A
authors.initials: NA
authors.lastname: Kulin
authors.forename: Deborah A
authors.initials: DA
authors.lastname: Marshall
mesh_terms: D000911:Antibodies, Monoclonal / Q000191:economics* / Q000627:therapeutic use; D061067:Antibodies, Monoclonal, Humanized; D000970:Antineoplastic Agents / Q000191:economics* / Q000627:therapeutic use; D002170:Canada; D017024:Chemotherapy, Adjuvant / Q000191:economics; D003365:Costs and Cost Analysis / Q000379:methods; D003657:Decision Making; D006801:Humans; D058990:Molecular Targeted Therapy; D000068878:Trastuzumab; D006113:United Kingdom; D014481:United States
chemical_list: D000911:Antibodies, Monoclonal; D061067:Antibodies, Monoclonal, Humanized; D000970:Antineoplastic Agents; D000068878:Trastuzumab