BACKGROUND: Rates of nonadherence to aromatase inhibitors (AIs) among Medicare beneficiaries with hormone receptor-positive early breast cancer are high. Out-of-pocket drug costs appear to be an important contributor to this and may be addressed by eliminating copayments and other forms of patient cost sharing. The authors estimated the incremental cost-effectiveness of providing Medicare beneficiaries with full prescription coverage for AIs compared with usual prescription coverage under the Medicare Part D program. METHODS: A Markov state-transition model was developed to simulate AI use and disease progression in a hypothetical cohort of postmenopausal Medicare beneficiaries with hormone receptor-positive early breast cancer. The analysis was conducted from the societal perspective and considered a lifetime horizon. The main outcome was an incremental cost-effectiveness ratio, which was measured as the cost per quality-adjusted life-year (QALY) gained. RESULTS: For patients receiving usual prescription coverage, average quality-adjusted survival was 11.35 QALYs, and lifetime costs were $83,002. For patients receiving full prescription coverage, average quality-adjusted survival was 11.38 QALYs, and lifetime costs were $82,728. Compared with usual prescription coverage, full prescription coverage would result in greater quality-adjusted survival (0.03 QALYs) and less resource use ($275) per beneficiary. From the perspective of Medicare, full prescription coverage was cost-effective (incremental cost-effectiveness ratio, $15,128 per QALY gained) but not cost saving. CONCLUSIONS: Providing full prescription coverage for AIs to Medicare beneficiaries with hormone receptor-positive early breast cancer would both improve health outcomes and save money from the societal perspective.
BACKGROUND: Rates of nonadherence to aromatase inhibitors (AIs) among Medicare beneficiaries with hormone receptor-positive early breast cancer are high. Out-of-pocket drug costs appear to be an important contributor to this and may be addressed by eliminating copayments and other forms of patient cost sharing. The authors estimated the incremental cost-effectiveness of providing Medicare beneficiaries with full prescription coverage for AIs compared with usual prescription coverage under the Medicare Part D program. METHODS: A Markov state-transition model was developed to simulate AI use and disease progression in a hypothetical cohort of postmenopausal Medicare beneficiaries with hormone receptor-positive early breast cancer. The analysis was conducted from the societal perspective and considered a lifetime horizon. The main outcome was an incremental cost-effectiveness ratio, which was measured as the cost per quality-adjusted life-year (QALY) gained. RESULTS: For patients receiving usual prescription coverage, average quality-adjusted survival was 11.35 QALYs, and lifetime costs were $83,002. For patients receiving full prescription coverage, average quality-adjusted survival was 11.38 QALYs, and lifetime costs were $82,728. Compared with usual prescription coverage, full prescription coverage would result in greater quality-adjusted survival (0.03 QALYs) and less resource use ($275) per beneficiary. From the perspective of Medicare, full prescription coverage was cost-effective (incremental cost-effectiveness ratio, $15,128 per QALY gained) but not cost saving. CONCLUSIONS: Providing full prescription coverage for AIs to Medicare beneficiaries with hormone receptor-positive early breast cancer would both improve health outcomes and save money from the societal perspective.
Authors: Dawn L Hershman; Jennifer Tsui; Jay Meyer; Sherry Glied; Grace Clarke Hillyer; Jason D Wright; Alfred I Neugut Journal: J Natl Cancer Inst Date: 2014-10-27 Impact factor: 13.506
Authors: Caitlin C Murphy; Jasmin A Tiro; Gary W Jean; Bijal A Balasubramian; Carlos A Alvarez Journal: J Womens Health (Larchmt) Date: 2017-03-15 Impact factor: 2.681
Authors: Constantinos I Michaelidis; Michael J Fine; Chyongchiou Jeng Lin; Jeffrey A Linder; Mary Patricia Nowalk; Ryan K Shields; Richard K Zimmerman; Kenneth J Smith Journal: BMC Infect Dis Date: 2016-11-08 Impact factor: 3.090