title: Cost effectiveness of gene expression profiling for early stage breast cancer: a decision-analytic model.
abstract: BACKGROUND
  Gene expression profiling (GEP) is being used increasingly for risk stratification to identify women with lymph node-negative, estrogen receptor-positive, early stage breast cancer who are most likely to benefit from adjuvant chemotherapy. The authors of this report evaluated the cost effectiveness of recurrence score-guided treatment using 2 commercially available GEP tests, Oncotype DX (Genomic Health, Redwood City, Calif) and MammaPrint (Agendia Inc., Irvine, Calif), from a third-party payer's perspective.
  
  
  METHODS
  A 10-year Markov model was developed to compare the costs and quality-adjusted life-years (QALYs) of treatment decisions guided by either Oncotype DX or MammaPrint in a hypothetical cohort of women with early stage, lymph node-negative, estrogen receptor-positive breast cancer who may experience recurrence. Outcomes included no recurrence, recurrence, and death. The costs considered included gene test costs, the costs of adjuvant chemotherapy and other chemotherapy (including premedication, oncology visits, and monitoring for adverse events), the cost of treating recurrence, costs associated with the treatment of adverse events, and end-of-life care costs.
  
  
  RESULTS
  The model demonstrated that the patients who received the Oncotype DX test to guide treatment spent $27,882 (in US dollars) and gained 7.364 QALYs, whereas patients who received the MammaPrint test to guide treatment spent $21,598 and gained 7.461 QALYs. Sensitivity analyses demonstrated that the results were robust to changes in all parameters.
  
  
  CONCLUSIONS
  The model suggested that MammaPrint is a more cost-effective GEP test compared with Oncotype DX at a threshold willingness-to-pay of $50,000 per QALY. Because Oncotype DX is the most frequently used GEP in clinical practice in the United States, the authors concluded that the current findings have implications for health policy, particularly health insurance reimbursement decisions.
authors.affiliation: Program in Personalized Medicine and Targeted Therapeutics, University of the Sciences, Philadelphia, PA 19104, USA.
authors.forename: Mo
authors.initials: M
authors.lastname: Yang
authors.forename: Suja
authors.initials: S
authors.lastname: Rajan
authors.forename: Amalia M
authors.initials: AM
authors.lastname: Issa
mesh_terms: D001943:Breast Neoplasms / Q000191:economics* / Q000235:genetics; D003362:Cost-Benefit Analysis; D020869:Gene Expression Profiling / Q000191:economics* / Q000379:methods*; D006801:Humans; D008390:Markov Chains; D012680:Sensitivity and Specificity