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中国直接口服抗凝剂与维生素K拮抗剂治疗静脉血栓栓塞症的成本效益分析

Cost-Effectiveness Analysis of Direct Oral Anticoagulants Versus Vitamin K Antagonists for Venous Thromboembolism in China.

作者信息

Sun Ke-Xin, Cui Bin, Cao Shan-Shan, Huang Qi-Xiang, Xia Ru-Yi, Wang Wen-Jun, Wang Jing-Wen, Yu Feng, Ding Yi

机构信息

Department of Pharmacy, Xijing Hospital, Fourth Military Medical University, Xi'an, China.

School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China.

出版信息

Front Pharmacol. 2021 Oct 20;12:716224. doi: 10.3389/fphar.2021.716224. eCollection 2021.

DOI:10.3389/fphar.2021.716224
PMID:34744710
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8563621/
Abstract

The drug therapy of venous thromboembolism (VTE) presents a significant economic burden to the health-care system in low- and middle-income countries. To understand which anticoagulation therapy is most cost-effective for clinical decision-making , the cost-effectiveness of apixaban (API) versus rivaroxaban (RIV), dabigatran (DAB), and low molecular weight heparin (LMWH), followed by vitamin K antagonist (VKA), in the treatment of VTE in China was assessed. To access the quality-adjusted life-years (QALYs) and incremental cost-effectiveness ratios (ICERs), a long-term cost-effectiveness analysis was constructed using a Markov model with 5 health states. The Markov model was developed using patient data collected from the Xijing Hospital from January 1, 2016 to January 1, 2021. The time horizon was set at 30 years, and a 6-month cycle length was used in the model. Costs and ICERs were reported in 2020 U.S. dollars. One-way sensitivity analysis and probabilistic sensitivity analysis (PSA) were used to test the uncertainties. A Chinese health-care system perspective was used. In the base case, the data of 231 VTE patients were calculated in the base case analysis retrospectively. The RIV group resulted in a mean VTE attributable to 95% effective treatment. API, DAB, and VKA have a negative ICER (-187017.543, -284,674.922, and -9,283.339, respectively) and were absolutely dominated. The Markov model results confirmed this observation. The ICER of the API and RIV was negative (-216176.977), which belongs to the absolute inferiority scheme, and the ICER value of the DAB and VKA versus RIV was positive (110,577.872 and 836,846.343). Since the ICER of DAB and VKA exceeds the threshold, RIV therapy was likely to be the best choice for the treatment of VTE within the acceptable threshold range. The results of the sensitivity analysis revealed that the model output varied mostly with the cost in the DAB on-treatment therapy. In a probabilistic sensitivity analysis of 1,000 patients for 30 years, RIV has 100% probability of being cost-effective compared with other regimens when the WTP is $10973 per QALY. When WTP exceeded $148,000, DAB was more cost-effective than RIV. Compared with LMWH + VKA and API, the results proved that RIV may be the most cost-effective treatment for VTE patients in China. Our findings could be helpful for physicians in clinical decision-making to select the appropriate treatment option for VTE.

摘要

静脉血栓栓塞症(VTE)的药物治疗给低收入和中等收入国家的医疗保健系统带来了巨大的经济负担。为了确定哪种抗凝治疗在临床决策中最具成本效益,评估了在中国治疗VTE时,阿哌沙班(API)与利伐沙班(RIV)、达比加群(DAB)和低分子肝素(LMWH),以及随后的维生素K拮抗剂(VKA)的成本效益。为了获取质量调整生命年(QALYs)和增量成本效益比(ICERs),使用具有5种健康状态的马尔可夫模型构建了长期成本效益分析。该马尔可夫模型是根据2016年1月1日至2021年1月1日从西京医院收集的患者数据开发的。时间范围设定为30年,模型中使用的周期长度为6个月。成本和ICERs以2020年美元报告。采用单向敏感性分析和概率敏感性分析(PSA)来测试不确定性。采用中国医疗保健系统的视角。在基础案例中,回顾性计算了231例VTE患者的基础案例分析数据。RIV组导致平均VTE归因于95%的有效治疗。API、DAB和VKA的ICER为负(分别为-187017.543、-284674.922和-9283.339),被绝对主导。马尔可夫模型结果证实了这一观察结果。API和RIV的ICER为负(-216176.977),属于绝对劣势方案,DAB和VKA与RIV相比的ICER值为正(110577.872和836846.343)。由于DAB和VKA的ICER超过阈值,RIV治疗可能是在可接受阈值范围内治疗VTE的最佳选择。敏感性分析结果显示,模型输出主要随DAB治疗期成本的变化而变化。在对1000名患者进行30年的概率敏感性分析中,当每QALY的意愿支付(WTP)为10973美元时,与其他方案相比,RIV具有100%的成本效益可能性。当WTP超过148000美元时,DAB比RIV更具成本效益。与LMWH + VKA和API相比,结果证明RIV可能是中国VTE患者最具成本效益的治疗方法。我们的研究结果可能有助于医生在临床决策中为VTE选择合适的治疗方案。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b564/8563621/3ede3a2a555a/fphar-12-716224-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b564/8563621/d585c9de9b3c/fphar-12-716224-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b564/8563621/d585c9de9b3c/fphar-12-716224-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b564/8563621/fe4a9ea7f5e4/fphar-12-716224-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b564/8563621/421fd9d9fbfb/fphar-12-716224-g003.jpg
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