Abstract
Background
Previous investigations into the cost effectiveness of direct oral anticoagulants only considered individual stroke risk but not bleed risk even though bleeding is an important and potentially fatal side effect for anticoagulated patients.
Objective
This study aimed to evaluate the cost effectiveness of dabigatran, rivaroxaban, apixaban, and edoxaban vs warfarin in patients with atrial fibrillation with varying stroke/bleed risk profiles over a lifetime horizon.
Methods
A Markov micro-simulation was adapted to examine the lifetime costs and quality-adjusted survival of five anticoagulants from a US private payer’s perspective. The study hypothetical cohort consisted of 10,000 patients with atrial fibrillation with age, CHA2DS2-VASc, and HAS-BLED scores similar to a commercially insured patient with atrial fibrillation cohort. Model input parameters including the efficacy and safety of each strategy, utilities, and cost were estimated from public sources, published literature, and analysis conducted in the IBM MarketScan database. Lifetime cost, quality-adjusted life-years, and incremental cost-effectiveness ratios were assessed for each treatment strategy. Subgroup analyses stratified by age, stroke risk score alone, bleed risk score alone and both were performed. Uncertainty was assessed by a deterministic sensitivity analysis and a probabilistic sensitivity analysis.
Results
The base-case analysis suggested dabigatran was the optimal treatment with an incremental cost-effectiveness ratio of $35,055 per quality-adjusted life-year relative to warfarin. Subgroup analyses stratified by age, stroke risk score, and bleed risk score alone were largely consistent with the base-case analysis. Subgroup analyses stratified by both stroke and bleed risk score showed edoxaban was the preferred treatment in patients with a low stroke and a low or medium bleed risk, and patients with a high stroke and low bleed risk. Apixaban was the preferred treatment in patients with a medium stroke and high bleed risk. Results of the deterministic sensitivity analysis indicate the model results were most sensitive to the drug cost and hazard ratio for stroke and bleeding event. Results of the probability sensitivity analysis showed dabigatran is cost effective vs. other treatments in 32.8% and 42.4% of iterations at a willingness to pay of $50,000/quality-adjusted life-year and a willingness to pay of $100,000/quality-adjusted life year, respectively.
Conclusions
From a US private payer’s perspective, dabigatran appears cost effective compared with other anticoagulants. This study indicated risk stratification especially considering both stroke and bleed risk simultaneously is important not only in clinical practice but also in health technology assessment exercises among patients with atrial fibrillation.
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No funding was received for the conduct of this study or the preparation of this article.
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Joshua D. Brown reports past private consulting fees from Pfizer, Inc. unrelated to the described project. Ching-Yu Wang, Phuong N. Pham, and Thuy N. Thai have no conflicts of interest that are directly relevant to the content of this article.
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For this type of study, formal consent is not required, thus we did not submit our study to an independent ethics committee or institutional review board. This article does not contain any studies with human participants or animals performed by any of the authors.
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The authors declare that all input data to parameterize the decision analytic model are available within the article. The model can be re-built entirely based on the detailed description of the model structure in the “Methods” section and information provided.
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Conceptualization, CYW and JB; methodology, CYW, PP, and JB; software, JB; validation, CYW, TT; formal analysis, CYW, PP; writing, original draft preparation, CYW; writing, review and editing, All authors; overall guarantor, JB.
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Wang, CY., Pham, P.N., Thai, T.N. et al. Updating the Cost Effectiveness of Oral Anticoagulants for Patients with Atrial Fibrillation Based on Varying Stroke and Bleed Risk Profiles. PharmacoEconomics 38, 1333–1343 (2020). https://doi.org/10.1007/s40273-020-00960-0
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DOI: https://doi.org/10.1007/s40273-020-00960-0