title: Cost effectiveness of molecular profiling for adjuvant decision making in patients with node-negative breast cancer.
abstract: OBJECTIVE
  To conduct an economic evaluation of the 70-gene signature used to guide adjuvant chemotherapy decision making both in patients with node-negative breast cancer (NNBC) and in the subgroup of estrogen receptor (ER) -positive patients.
  
  
  METHODS
  We used a mixed approach combining patient-level data from a multicenter validation study of the 70-gene signature (untreated patients) and secondary sources for chemotherapy efficacy, unit costs, and utility values. Three strategies on which to base the decision to administer adjuvant chemotherapy were compared: the 70-gene signature, Adjuvant! Online, and chemotherapy in all patients. In the base-case analysis, costs from the French National Insurance Scheme, life-years (LYs), and quality-adjusted life-years (QALYs) were computed for the three strategies over a 10-year period. Cost-effectiveness acceptability curves using the net monetary benefit were computed, combining bootstrap and probabilistic sensitivity analyses.
  
  
  RESULTS
  The mean differences in LYs and QALYs were similar between the three strategies. The 70-gene signature strategy was associated with a higher cost, with a mean difference of €2,037 (range, €1,472 to €2,515) compared with Adjuvant! Online and of €657 (95% CI, -€642 to €3,130) compared with systematic chemotherapy. For a €50,000 per QALY willingness-to-pay threshold, the probability of being the most cost-effective strategy was 92% (76% in ER-positive patients) for the Adjuvant! Online strategy, 6% (4% in ER-positive patients) for the systematic chemotherapy strategy, and 2% (20% in ER-positive patients) for the 70-gene strategy.
  
  
  CONCLUSIONS
  Optimizing adjuvant chemotherapy decision making based on the 70-gene signature is unlikely to be cost effective in patients with NNBC.
authors.affiliation: All authors: Gustave Roussy, Villejuif, France. julia.bonastre@gustaveroussy.fr.
authors.forename: Julia
authors.initials: J
authors.lastname: Bonastre
authors.affiliation: All authors: Gustave Roussy, Villejuif, France.
authors.forename: Sophie
authors.initials: S
authors.lastname: Marguet
authors.affiliation: All authors: Gustave Roussy, Villejuif, France.
authors.forename: Beranger
authors.initials: B
authors.lastname: Lueza
authors.affiliation: All authors: Gustave Roussy, Villejuif, France.
authors.forename: Stefan
authors.initials: S
authors.lastname: Michiels
authors.affiliation: All authors: Gustave Roussy, Villejuif, France.
authors.forename: Suzette
authors.initials: S
authors.lastname: Delaloge
authors.affiliation: All authors: Gustave Roussy, Villejuif, France.
authors.forename: Mahasti
authors.initials: M
authors.lastname: Saghatchian
mesh_terms: D000328:Adult; D014408:Biomarkers, Tumor / Q000032:analysis*; D001943:Breast Neoplasms / Q000188:drug therapy* / Q000235:genetics / Q000401:mortality; D017024:Chemotherapy, Adjuvant; D003362:Cost-Benefit Analysis; D003657:Decision Making; D005260:Female; D020869:Gene Expression Profiling / Q000191:economics* / Q000379:methods; D006801:Humans; D008875:Middle Aged; D019057:Quality-Adjusted Life Years; D015996:Survival Rate
chemical_list: D014408:Biomarkers, Tumor