第38届医疗决策学会年会。

Mette H Møller, M. L. Lousdal, I. Kristiansen, M. Kalager, Torbjørn, Wisløff
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引用次数: 0

摘要

5: SMDM第38届年会:温哥华,不列颠哥伦比亚省,加拿大E2 -医疗决策/ 2017年1月PS 1-2多发性硬化症疾病改善药物的健康经济评估应用卫生经济学(AHE)挪威奥斯陆公共卫生研究所Vida Hamidi博士,Elisabeth Couto博士和Marianne Klemp博士,医学博士,目的:多发性硬化症(MS)是年轻人最常见的致残原因之一。几种疾病修饰疗法(DMT)可用于治疗多发性硬化症,但不同治疗的成本效益尚未在挪威进行调查。方法:我们建立了一个概率决策模型来评估用于多发性硬化症的13种不同的DMT的成本效益,该模型使用状态转移方法模拟多发性硬化症的自然历史。根据Kurtzke EDSS(0-10)定义健康状态。在一个模型周期内,患者可能保持当前的健康状态,进展到下一个更严重的状态,过渡到继发性进行性健康状态,或死亡。EDDS评分为5或更低的患者也可能改善到较轻的状态,并经历复发。并发症也包括在模型中。过渡概率根据已发表的资料和临床专家的意见得出。每年复发和残疾进展的疗效估计是基于通过系统文献检索确定的已发表的随机对照试验的网络荟萃分析。生活质量数据是通过系统的文献检索从已发表的研究中提取的。治疗费用是根据挪威官方单位价格估计的。所有费用和健康福利均按每年4%的比率折现。采用蒙特卡罗模拟方法进行敏感性分析。结果:阿仑单抗比其他策略更有效,成本更低。排除阿仑单抗(主导策略)的情景分析显示,干扰素β -1b (Extavia)、peg-干扰素β -1a和natalizumab可能具有成本效益,这取决于支付意愿(WTP)阈值。假设每QALY获得的WTP低于107,000欧元,那么Extavia约有40%的可能性是最具成本效益的治疗方法,其次是聚乙二醇干扰素β -1a(约30%的可能性)。然而,对疗效和流行病学输入参数的更多研究将对减少决策不确定性产生最大的影响。结论:基于成本-效果分析结果的临床实践改变具有降低MS治疗相关成本的巨大潜力。应用卫生经济学(AHE) Phuc Le,博士,公共卫生硕士和Michael Rothberg,医学博士,公共卫生硕士,克利夫兰医学研究所,克利夫兰,俄亥俄州
本文章由计算机程序翻译,如有差异,请以英文原文为准。
38th Annual Meeting of the Society for Medical Decision Making.
s: SMDM 38th Annual Meeting: Vancouver, British Columbia, Canada E2  MEDICAL DECISION MAKING/JANUARY 2017 PS 1-2 HEALTH ECONOMIC EVALUATION OF DISEASE MODIFYING MEDICINES USED FOR MULTIPLE SCLEROSIS Applied Health Economics (AHE) Vida Hamidi, Ph.D, Elisabeth Couto, PhD and Marianne Klemp, MD, PhD, Norwegian Institute of Public Health, Oslo, Norway Purpose: Multiple sclerosis (MS) is one of the most common causes of disability in young adults. Several disease-modifying therapies (DMT) are available for the treatment of MS, but the cost-effectiveness of the different treatments has not been investigated in a Norwegian setting. To ensure the most appropriate MS management, it is important to assess cost-effectiveness of disease modifying medicines used for MS. Method: We developed a probabilistic decision model to assess the cost-effectiveness of thirteen different DMT used for MS. The model simulates the natural history of MS using the state transition methodology. Health states were defined according to the Kurtzke EDSS (0-10). During one model cycle, patients could remain in the current health state, progress to the next more severe state, transition to a secondary-progressive health state, or die. Patients with an EDDS scale of five or lower could also improve to a less severe state, and experience relapse. Complications were also included in the model. Transitional probabilities were derived from published sources and clinical experts’ opinions. Efficacy estimates for annual relapse and disability progression were based on the network meta-analyses of published RCTs identified by a systematic literature search. Quality of life data were extracted from published studies based on a systematic literature search. Treatment costs were estimated based on official Norwegian unit prices. All costs and health benefits were discounted at a rate of 4% per annum. Sensitivity analysis was performed by means of Monte Carlo simulation. Result: Alemtuzumab was more effective and less costly than the other strategies. A scenario analysis that excluded alemtuzumab (the dominant strategy) showed that interferon beta-1b (Extavia), peg-interferon beta-1a and natalizumab could be cost-effective depending on the willingness-to-pay (WTP) threshold. Assuming a WTP below EUR107,000 per QALY gained, Extavia was approximately 40% likely to be the most cost-effective treatment, followed by peginterferon beta-1a (approximately 30% likely). However, more research on efficacy and epidemiologic input parameters would have the greatest impact on reducing decision uncertainty. Conclusion: Change in clinical practice based on the results of cost-effectiveness analysis has a substantial potential to reduce costs associated with MS treatment. PS 1-3 USING COST-EFFECTIVENESS ANALYSIS TO DETERMINE A THRESHOLD FOR VENOUS THROMBOEMBOLISM PROPHYLAXIS IN HOSPITALIZED MEDICAL PATIENTS Applied Health Economics (AHE) Phuc Le, PhD, MPH and Michael Rothberg, MD, MPH, Medicine Institute Cleveland Clinic, Cleveland, OH
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