A Comprehensive Probabilistic-Micro-Simulation Model to Assess Cost-Effectiveness

描述(申请人提供)：精神分裂症影响约1.3%的人口，但每年造成280亿美元的医疗费用。精神分裂症给患者、患者家属和社会带来的负担很大。抗精神病药物是精神分裂症的一线治疗药物，帮助一些患有这种疾病的患者过上了富有成效和满足感的生活。随着第二代抗精神病药物的出现，通常比第一代抗精神病药物昂贵得多，这些患者的医疗费用增长稳步上升，这让人质疑较新的第二代抗精神病药物(非典型药物)相对于老一代抗精神病药物的边际价值。关于药品支出是否能抵消这些患者昂贵的住院治疗，也没有明确的证据。因此，关于使用这些更新和更昂贵的药物的争议越来越大，特别是当其中一些药物最近证明在这个本已脆弱的人群中心血管风险增加的证据时。最近发表的NIMH资助的CATIE研究结果进一步推动了这场辩论，该研究报告了随机接受第一代抗精神病药物与非典型抗精神病药物的患者之间的续用率相等。在存在这样的争议的情况下，仍然有一些关键的问题需要回答。这些问题涉及目前和未来的各种政策，影响着广泛的利益相关者，主要集中在非典型药物与抗精神病药物的比较有效性、成本和成本效益上。只有仔细研究评估精神分裂症的治疗方案并确定这一领域的研究重点，才能回答这些问题。这项提案试图使用经济学、统计学和决策科学的创新方法来解决这些问题。在这项工作中，我们建议在精神分裂症中开发和应用一个全面的概率微模拟模型，以提供关于人群水平的成本、药物治疗的有效性和成本效益以及治疗算法的信息。本文提出的工作具有重要的方法论和临床意义。所提出的方法进步将在卫生保健的许多领域中对技术评估具有重要应用，并希望为其在许多其他背景下的潜在应用提供有价值的见解。在临床上，我们的发现为医生和他们的患者提供了关于治疗结果分布的丰富信息，有助于指导他们做出更明智的治疗选择，从而有可能对精神分裂症的治疗产生重要影响。此外，信息分析的拟议价值将指导这一领域的未来研究和资源，方法是确定对哪些参数进行更准确的估计最有价值的研究优先事项。面对不断上涨的成本和对新药疗效的模糊证据，关于精神分裂症患者使用第二代抗精神病药物与第一代抗精神病药物的争议越来越大。频繁地在替代药物之间切换表明，可能没有一种药物对患者来说是最佳的。目前对治疗效果的估计存在巨大的不确定性，这意味着该领域未来研究的价值可能是巨大的。为了解决这些问题，拟议的工作旨在开发一个全面的微观模拟模型，以评估精神分裂症替代药物治疗算法的成本、有效性和成本效益，并进行这一领域未来研究分析的信息价值和价值。

DESCRIPTION (provided by applicant): Schizophrenia affects about 1.3% of the population and yet is responsible for US$28 billion in annual health care costs. The burden of schizophrenia to the patients, their family members and to the society is large. Antipsychotic drugs are the first line of treatment of schizophrenia and have helped some patients with this disease to lead productive and fulfilling lives. With the advent of the second-generation of antipsychotic drugs, which are typically much more expensive than first generation antipsychotics, the growth in medical expenditures among these patients have risen steadily, calling into question the marginal value of the newer second-generation antipsychotic drugs (atypicals) over the older generation neuroleptics. There is also ambiguous evidence on whether pharmaceutical expenditures can offset the expensive inpatient care for these patients. Consequently, controversies are growing regarding the use of these newer and more expensive drugs, especially when some of them have recently documented evidence of increasing cardiovascular risks in this already vulnerable population. This debate is further fueled by the recently published results from the NIMH funded CATIE study that reported equivalence of continuation rates between patient randomized to receiving first-generation versus atypical antipsychotic drugs. In the presence of such controversy, there remain crucial questions to be answered. These questions span a variety of policies, both present and future, influence a wide range of stake-holders, and primarily focus on the comparative effectiveness, costs and cost-effectiveness of the atypicals versus the neuroleptics. They can only be answered with careful research on evaluating treatment options in schizophrenia and identifying research priorities in this field. This proposal attempts to address these questions using innovative methods in economics, statistics and decision sciences. In this work, we propose to develop and apply a comprehensive probabilistic micro-simulation model in schizophrenia to provide information about population level costs, effectiveness and cost-effectiveness of pharmacological treatments and treatment algorithms. The work proposed here is important methodologically and clinically. The methodological advancements that are proposed will have major applications for technology assessment in many domains in health care and hope to provide valuable insights for their potential application in many other contexts. Clinically, our findings have the potential to have important implications for the treatment of schizophrenia by providing physicians and their patients with rich information on the distribution of outcomes of treatments that can help guide them in making more informed treatment choices. Furthermore, the proposed value of information analyses will direct future research and resources in this field by identifying research priorities on those parameters where more precise estimates would be most valuable. Controversies are growing regarding the use of second generation versus the first generation antipsychotics by patients with schizophrenia in the face of rising costs and ambiguous evidence on the benefits of the newer drugs. Frequent switching between alternative drugs indicates that no one drug may be optimal for a patient. Enormous uncertainties in current estimates of treatment effect imply that the value of future research in this filed may be substantial. In order to address these questions, the proposed work aims to develop a comprehensive micro-simulation model to assess the costs, effectiveness, cost-effectiveness of alternative pharmacological treatment algorithms in schizophrenia and to conduct value of information and value of future research analyses in this field.