期刊
INTERNATIONAL JOURNAL OF CARDIOLOGY
卷 282, 期 -, 页码 53-58出版社
ELSEVIER IRELAND LTD
DOI: 10.1016/j.ijcard.2018.11.087
关键词
Rivaroxaban; Warfarin; Cost-effectiveness; Nonvalvular atrial fibrillation; Markov model; Worsening renal function
资金
- USC Graduate School
- USC School of Pharmacy
Background: Nonvalvular atrial fibrillation (NVAF) is highly prevalent and increases the risks of cardiovascular events. In a recent subgroup analysis, treatment response was shown W vary for patients exhibiting worsening renal function (WRF) on-Ixeatment. It is important to understand the cost-effectiveness of novel oral anticoagulant (NOAC) use in this population. Methods: A cost-effectiveness analysis (CEA) was conducted using a Markov model to determine whether NOAC rivaroxaban treatment is cost-effective relative W warfarin in NVAF patients with on-treatment WRF. Input parameters were sourced from clinical literature including a multicenter clinical trial and subgroup analysis. We studied elderly US male patients at increased risk for stroke (CHADS2 score L- 2) undergoing treatment for NVAF and exhibiting WRF. Main outcome measures included total healthcare costs in 2017 US dollars (societal perspective), total quality-adjusted life years (QALYs), incremental cost-effectiveness ratio (ICER), and incremental net monetary benefits (INMB) per-patient. Results: The remaining lifetime use of rivaroxaban is associated with 5.69 QALYs at a cost of $66,075 per patient, while warfarin produced 5.22 QALYs with costs of $78,504 per patient. At a willingness-to-pay (WTP) of $150,000 per QALY, incremental net monetary benefits (INMB) per patient are $83,590. In our population, treatment with warfarin was dominated by rivaroxaban in 99.4% of 10,000 simulations. Conclusions: Rivaroxaban is likely a dominant treatment over warfarin in elderly US male NVAF patients exhibiting WRF, providing increased QALYs at a decreased overall cost. Application of these findings may require healthcare providers to predict which patients are likely to exhibit WRF. (C) 2018 Elsevier B.V. All rights reserved.
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