Adelaide Health Technology Assessment, Discipline of Public Health, School of Population Health and Clinical Practice, University of Adelaide, Adelaide, South Australia, Australia (TM, CF, CS)
Australian Government Department of Health and Ageing, Canberra, Australian Capital Territory, Australia (AM)
Med Decis Making. 2013 Apr;33(3):333-42. doi: 10.1177/0272989X12452341. Epub 2012 Aug 15.
Since the mapping of the human genome in 2003, the development of biomarker targeted therapy and clinical adoption of "personalized medicine" has accelerated. Models for insurance subsidy of biomarker/test/drug packages ("codependent technologies" or technologies that work better together) are not well developed. Our aim was to create a framework to assess the safety, effectiveness, and cost-effectiveness of these technologies for a national coverage or reimbursement decision.
We extracted information from assessments of recent Australian reimbursement applications that concerned genetic tests and treatments to identify items and evidence gaps considered important to the decision-making process. Relevant international regulatory and reimbursement guidance documents were also reviewed. Items addressing causality theory were included to help explain the relationship between biomarker and treatment. The framework was reviewed by policy makers and technical experts, prior to a public consultation process.
The framework consists of 5 components--context, clinical benefit, evidence translation, cost-effectiveness, and financial impact--and a checklist of 79 items. To determine whether the biomarker test, the drug, both, or neither should be subsidized, we considered it crucial to identify whether the biomarker is a treatment effect modifier or a prognostic factor. To aid in this determination, the framework explicitly allows the linkage of different types of evidence to examine whether targeting the biomarker varies the likely clinical benefit of the drug, and if so, to what extent.
The first national framework to assess personalized medicine for coverage or reimbursement decisions has been developed and introduced and may be a suitable model for other health systems.
自 2003 年人类基因组图谱绘制完成以来,生物标志物靶向治疗的发展和“个性化医学”的临床应用都在加速。针对生物标志物/检测/药物组合(“相依技术”或协同作用更好的技术)的保险补贴模式尚未得到充分发展。我们的目标是创建一个框架,以评估这些技术对于国家覆盖范围或报销决策的安全性、有效性和成本效益。
我们从最近澳大利亚报销申请的评估中提取了与基因检测和治疗有关的信息,以确定对决策过程重要的项目和证据差距。还审查了相关的国际监管和报销指南文件。纳入了涉及因果关系理论的项目,以帮助解释生物标志物与治疗之间的关系。在公众咨询过程之前,该框架已经由政策制定者和技术专家进行了审查。
该框架由 5 个部分组成——背景、临床获益、证据转化、成本效益和财务影响——以及一份包含 79 个项目的检查表。为了确定生物标志物检测、药物、两者或两者都应得到补贴,我们认为必须确定生物标志物是治疗效果修饰剂还是预后因素。为了帮助做出这一决定,该框架明确允许链接不同类型的证据,以检查针对生物标志物是否会改变药物的临床获益,以及如果会改变,程度如何。
已经开发并引入了首个用于评估个性化医学覆盖范围或报销决策的国家框架,它可能是其他卫生系统的合适模式。