Abstract P5-11-15: Modeling for Response Predictive Factors in Adjuvant Endocrine Therapy: Impact on Preferential Benefits of Tamoxifen and Aromatase Inhibitors
Authors: T Younis, D Rayson, C. Skedgel
Journal: Cancer Research (2010)

Abstract Background: The Early Breast Cancer Trialists’ Collaborative Group (EBCTCG) observed significant improvements in breast cancer (BC) outcomes following adjuvant tamoxifen (TAM) and/or aromatase inhibitor (AI) therapy relative to natural history (NH) without endocrine therapy. In unselected populations, upfront AI for 5-years appears to be associated with improved disease-free survival (DFS) relative to 5-years of TAM alone. BC outcomes for TAM and AI in the EBCTCG meta-analyses, however, may reflect composite outcomes for heterogeneous sub populations of patients with varying responsiveness to TAM and AI's. A number of studies suggest that response to endocrine therapy (excellent vs poor) with TAM (TAM-excellent vs TAM-poor responders) and AI (AI-excellent vs AI-poor responders) may be related to TAM metabolizer status (non impaired vs impaired) and body mass index (normal vs high), respectively. This study examines the potential impact of these predictive factors on BC outcomes following TAM or AI therapy to determine the adjuvant endocrine monotherapy associated with improved BC outcomes for postmenopausal women with breast cancer. Methods: A generic state-transition model was developed to compute BC outcomes over a 10-year horizon in hypothetical cohorts of postmenopausal women receiving 5-years of adjuvant TAM (TAM cohort) or AI (AI cohort) or no endocrine therapy (NH cohort). We estimated DFS rates and cumulative life-years associated with NH, TAM and AI in unselected cohorts as well as sub-cohorts with varying responsiveness to TAM or AI. BC outcomes in the unselected cohorts were derived from the EBCTCG meta-analyses. BC outcomes in the sub-cohorts of TAM-excellent vs TAM-poor responders and AI-excellentvs AI-poor responders were based on varying combinations of responder proportions (excellent vs poor) and odd ratios (ORs) of BC outcomes in excellent vs poor responders that are plausible within the composite BC outcomes observed in the unselected TAM and AI cohorts. The model assumes that BC outcomes in poor responders could not be worse than BC outcomes for NH. Sensitivity analyses were conducted, and the impact of varying 10-year baseline recurrence risk without endocrine therapy was examined to reflect the natural spectrum of breast cancer disease encountered. Results: Two-way sensitivity analyses are provided for TAM and AI predictive factors to determine which adjuvant endocrine therapy (TAM vs AI) may be associated with improved BC outcomes based on the prevalence of the response predictive factors and their relative impact on BC outcomes. The plausible combinations of prevalence and OR for TAM excellent responders in the TAM cohort as well as AI poor responders in the AI cohort that predict improved BC outcomes with TAM relative to AI monotherapy are provided. Sensitivity analyses will be presented. Conclusions: Adjuvant endocrine monotherapy with TAM may be associated with improved BC outcomes in TAM-excellent responders compared to an unselected AI cohort or in an unselected TAM cohort compared to AI-poor responders. The choice of optimal adjuvant endocrine therapy may depend upon the prevalence of treatment predictive factors and their relative impact on BC outcomes. Citation Information: Cancer Res 2010;70(24 Suppl):Abstract nr P5-11-15.