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Cost effectiveness of gene expression profiling for early stage breast cancer †
A decision-analytic model
Article first published online: 6 JUN 2012
Copyright © 2012 American Cancer Society
Volume 118, Issue 24, pages 6298–6299, 15 December 2012
How to Cite
Reed, S. D. and Lyman, G. H. (2012), Cost effectiveness of gene expression profiling for early stage breast cancer . Cancer, 118: 6298–6299. doi: 10.1002/cncr.27665
- Issue published online: 3 DEC 2012
- Article first published online: 6 JUN 2012
In a recently published cost-effectiveness analysis by Yang et al,1 the authors compared Oncotype DX (Genomic Health, Redwood City, Calif) versus MammaPrint (Agendia Inc USA, Irvine, Calif) for guiding the use of chemotherapy in patients with early-stage, estrogen receptor-positive breast cancer. Such a head-to-head comparison is consistent with the spirit of comparative effectiveness research, which the Institute of Medicine defines as “the generation and synthesis of evidence that compares the effectiveness of alternative methods to prevent, diagnose, treat, monitor, and improve delivery of care for a clinical condition.”2 The analysts developed a decision-analytic model to evaluate expected costs and quality-adjusted survival over a 10-year period. Recognizing that treatment preferences are not driven entirely by results from gene expression profiling, the analysts first classified patients in the decision tree as being at low or high risk according to Adjuvant! Online, which uses patient and tumor characteristics for risk stratification. They then cross-stratified patients according to Oncotype DX or MammaPrint risk level.
Although this structure is appropriate, the analysts assumed that 47% of patients in the Oncotype DX group and 74% of patients in the MammaPrint group were at high risk according to Adjuvant! Online. This assumption made for an unfair comparison between genetic tests. For a fair comparison, patients in both groups should have the same risk according to Adjuvant ! Online. Because the majority of women with high-risk clinicopathologic characteristics (according to Adjuvant! Online) also have high-risk genetic markers (61% with Oncotype DX and 73% with MammaPrint), more women receiving MammaPrint would have been expected to receive chemotherapy and therefore incur higher costs. However, despite the higher costs associated with MammaPrint testing ($4200 vs $3975), Yang et al1 reported lower expected costs with MammaPrint over 10 years ($21,598 vs $27,882). The authors reported neither the percentage of women receiving chemotherapy nor the percentage of women with distant disease recurrence. Therefore, it is not clear how cost savings were achieved with MammaPrint compared with Oncotype DX.
For the expectations of comparative effectiveness research to be realized, the careful use of methodological tools such as decision analysis will be necessary to make fair head-to-head comparisons between technologies outside the context of randomized clinical trials. In the case of cost-effectiveness models, reporting should go beyond the presentation of expected costs and quality-adjusted life-years and include estimates of intermediate end points such as treatment rates and the incidence of disease recurrence.
Note Added in Proof
CONFLICT OF INTEREST DISCLOSURES
Drs. Reed and Lyman reported receiving research support from Amgen, Inc, and Genomic Health. Dr Reed has acted as a consultant for Abbott Laboratories; Celladon Corporation; Eisai, Inc; and Helsinn Therapeutics (US), Inc and has received research grants from Actelion Pharmaceuticals Ltd; Alnylam Pharmaceuticals, Inc; Amylin Pharmaceuticals, Inc; Arthritis Foundation; Astellas Pharma, Inc; Bristol-Myers Squibb Company; Dendreon Corporation; Genomic Health, Inc; Helsinn Therapeutics (US), Inc; and Inspire Pharmaceuticals, Inc.
- 1Cost effectiveness of gene expression profiling for early stage breast cancer: a decision-analytic model [published online ahead of print February 22, 2012]. Cancer. doi: 10.1002/cncr.27443., , .
- 2Institute of Medicine. Initial National Priorities for Comparative Effectiveness Research. Washington, DC: National Academies Press; 2009.