The economic and clinical outcomes and policy implications of gene expression profiling in breast cancer care
In the U.S., the majority of premenopausal breast cancer patients are recommended by clinical guidelines to receive adjuvant chemotherapy to prevent disease progression and increase survival. However, low-risk patients may be experiencing the side effects of chemotherapy, with no corresponding benefit, which may also lead to spending on unnecessary treatment by healthcare payers. In response to this situation, new genomic assays have been marketed or are in development that profile the biology of the tumor cells and may be better able to identify high-risk patients than the current guidelines. However, the clinical, economic and patient outcomes associated with these approaches are unknown. We compared the cost-utility of one of these genomic assays developed by investigators at the Netherlands Cancer Institute to NIH guidelines in a cohort of 44 year-old women with early stage breast cancer. We utilized a decision analytic model that was informed by empiric and literature-based estimates, and model parameters were varied in sensitivity analyses. As an input to the decision model, the costs of adjuvant chemotherapy have a large influence on results. Thus, an accurate estimate of these costs was needed. We conducted a cost study to estimate the direct medical costs of adjuvant chemotherapy in this young patient population to inform the decision model and to better understand the economic burden of this treatment modality. We estimated these costs to be $21,684, so they constitute a substantial component of breast cancer treatment costs. For the cost-utility analysis, we found that the genomic assay was much more specific, but less sensitive than NIH guidelines in detecting high-risk women. As a result, the improvement in quality of life due to avoiding chemotherapy appeared to be offset by an increased risk of breast cancer progression. It appears that these genomic assays, which have yet to be validated or demonstrated to be in equipoise with current NIH guidelines, require additional refinement and validation before implementation in clinical practice. Our study highlights the value of cost-utility analysis in clarifying the tradeoffs between life expectancy, quality of life and costs in the era of genetic assays.
- Pharmaceutics