Economic evaluation of hormonal therapies for postmenopausal women with estrogen receptor-positive early breast cancer in Canada

加拿大对绝经后雌激素受体阳性早期乳腺癌女性激素疗法的经济评估

阅读:1

Abstract

BACKGROUND: Aromatase inhibitor (ai) therapy has been subjected to numerous cost-effectiveness analyses. However, with most ais having reached the end of patent protection and with maturation of the clinical trials data, a re-analysis of ai cost-effectiveness and a consideration of ai use as part of sequential therapy is desirable. Our objective was to assess the cost-effectiveness of the 5-year upfront and sequential tamoxifen (tam) and ai hormonal strategies currently used for treating patients with estrogen receptor (er)-positive early breast cancer. METHODS: The cost-effectiveness analysis used a Markov model that took a Canadian health system perspective with a lifetime time horizon. The base case involved 65-year-old women with er-positive early breast cancer. Probabilistic sensitivity analyses were used to incorporate parameter uncertainties. An expected-value-of-perfect-information test was performed to identify future research directions. Outcomes were quality-adjusted life-years (qalys) and costs. RESULTS: The sequential tam-ai strategy was less costly than the other strategies, but less effective than upfront ai and more effective than upfront tam. Upfront ai was more effective and less costly than upfront tam because of less breast cancer recurrence and differences in adverse events. In an exploratory analysis that included a sequential ai-tam strategy, ai-tam dominated based on small numerical differences unlikely to be clinically significant; that strategy was thus not used in the base-case analysis. CONCLUSIONS: In postmenopausal women with er-positive early breast cancer, strategies using ais appear to provide more benefit than strategies using tam alone. Among the ai-containing strategies, sequential strategies using tam and an ai appear to provide benefits similar to those provided by upfront ai, but at a lower cost.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。