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

S. Djalalov, J. Beca, E. Amir, M. Krahn, M. E. Trudeau, Jeffrey S Hoch

Research output: Contribution to journalArticle

7 Citations (Scopus)

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 costeffectiveness 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 expectedvalue- 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.

Original languageEnglish (US)
Pages (from-to)84-96
Number of pages13
JournalCurrent Oncology
Volume22
Issue number2
DOIs
StatePublished - 2015
Externally publishedYes

Fingerprint

Aromatase Inhibitors
Cost-Benefit Analysis
Canada
Estrogens
Breast Neoplasms
Tamoxifen
Estrogen Receptors
Therapeutics
Costs and Cost Analysis
Quality-Adjusted Life Years
Uncertainty
Clinical Trials
Recurrence

Keywords

  • Aromatase inhibitors
  • Breast cancer
  • Cost-effectiveness
  • Tamoxifen

ASJC Scopus subject areas

  • Oncology

Cite this

Economic evaluation of hormonal therapies for postmenopausal women with estrogen receptor–positive early breast cancer in Canada. / Djalalov, S.; Beca, J.; Amir, E.; Krahn, M.; Trudeau, M. E.; Hoch, Jeffrey S.

In: Current Oncology, Vol. 22, No. 2, 2015, p. 84-96.

Research output: Contribution to journalArticle

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AB - 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 costeffectiveness 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 expectedvalue- 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.

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