Is adjuvant therapy for older patients with node (+) early breast cancer cost-effective?

Abstract

Background: Node (+) breast cancer represents over 40% of cases in older women and currently there is a debate whether adjuvant therapy for all older women is cost-effective.

Purpose: To evaluate if adjuvant treatment for early-stage (Stage I-IIIa) node (+) breast cancer with hormone therapy, chemotherapy, or combination therapy is cost-effective in older patients.

Design: A decision-analysis model for 65, 75, and 85 year-old female breast cancer patients using life tables integrated the cost of treatment in dollars and impact in length and quality of life. Both estrogen receptor (ER) (-) and (+) patients were considered. The primary data sources were meta-analysis from the Early Breast Cancer Trialists' Collaborative Group and the Red Book Average Wholesale Price for drugs. The cost of treatment in dollars and impact of quality of life was examined. Scenarios were used when treatment benefit was uncertain. The incremental cost-effectiveness of different treatment strategies were then compared and mapped graphically.

Results: Adjuvant therapy is cost-effective in 65 year-old women with early breast cancer. In a 75 year-old ER (+) patient, hormone therapy is cost-effective, $10,965/quality-adjusted life years (QALY), but chemotherapy was more cost-effective, $27,406/QALY, if one assumed it was as efficacious as in a 65 year-old woman. In a 75 year-old ER (-) patient, chemotherapy was cost-effective at $42,605 with the same assumption. In an 85 year-old ER (+) patient, hormone therapy was cost-effective, $26,463/QALY, if efficacy is not age-sensitive, but chemotherapy was not as cost-effective for either ER (+) or ER (-) patients.

Conclusion: Treatment decisions for older breast cancer patients suffer from the lack of sufficient clinical trial data. Decision-analytic models can help policy makers who are faced with decisions about whether to support adjuvant therapy in older breast cancer patients and also outline the important parameters that need to be considered in such a decision.