How to Appropriately Extrapolate Costs and Utilities in Cost-Effectiveness Analysis
How to Appropriately Extrapolate Costs and Utilities in Cost-Effectiveness Analysis
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DOI：
10.1007/s40273-017-0512-6
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发表时间：
2017-08-01
影响因子：
4.4
通讯作者：
Palmer, Stephen
中科院分区：
文献类型：
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作者：
Bojke, Laura;Manca, Andrea;Palmer, Stephen
成本和公用事业是任何成本效益分析的关键输入。他们的估计通常来自作为临床研究的一部分收集的个体患者水平数据，其随访时间通常太短，无法对技术在患者整个生命周期中产生的可能成本和收益进行稳健的量化。在缺乏长期数据的情况下，需要某种形式的时间外推，以便在较长的时间范围内预测短期证据。时间外推不可避免地涉及关于临床证据支持的时间范围之外的感兴趣量的行为的假设。不幸的是，根据这种做法得出的证据所作的决定的影响以及围绕任何假设的有效性的不确定程度往往没有得到充分的认识。由于缺乏关于费用和公用事业等非即时结果外推的方法指导，这一问题更加复杂。本文考虑了目前预测长期成本和效用的方法，强调了现有方法的一些挑战，并为未来的应用提供了建议。它发现，通常情况下，经济评估模型采用简单的方法来时间外推的成本和效用。例如，它们的参数（例如，平均值）通常被假设为关于时间和患者的特征是均匀的。此外，成本和公用事业往往被建模，以遵循相关的时间到事件的结果的动态。然而，成本和效用估计可能更加微妙，重要的是要确保对这些参数进行适当的外推。
Costs and utilities are key inputs into any cost-effectiveness analysis. Their estimates are typically derived from individual patient-level data collected as part of clinical studies the follow-up duration of which is often too short to allow a robust quantification of the likely costs and benefits a technology will yield over the patient's entire lifetime. In the absence of long-term data, some form of temporal extrapolation-to project short-term evidence over a longer time horizon-is required. Temporal extrapolation inevitably involves assumptions regarding the behaviour of the quantities of interest beyond the time horizon supported by the clinical evidence. Unfortunately, the implications for decisions made on the basis of evidence derived following this practice and the degree of uncertainty surrounding the validity of any assumptions made are often not fully appreciated. The issue is compounded by the absence of methodological guidance concerning the extrapolation of non-time-to-event outcomes such as costs and utilities. This paper considers current approaches to predict long-term costs and utilities, highlights some of the challenges with the existing methods, and provides recommendations for future applications. It finds that, typically, economic evaluation models employ a simplistic approach to temporal extrapolation of costs and utilities. For instance, their parameters (e.g. mean) are typically assumed to be homogeneous with respect to both time and patients' characteristics. Furthermore, costs and utilities have often been modelled to follow the dynamics of the associated time-to-event outcomes. However, cost and utility estimates may be more nuanced, and it is important to ensure extrapolation is carried out appropriately for these parameters.