How to Appropriately Extrapolate Costs and Utilities in Cost-Effectiveness Analysis
Laura Bojke (),
Miqdad Asaria (),
Shijie Ren and
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Laura Bojke: University of York
Andrea Manca: University of York
Ronan Mahon: University of York
Shijie Ren: University of Sheffield
Stephen Palmer: University of York
PharmacoEconomics, 2017, vol. 35, issue 8, No 3, 767-776
Abstract 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.
Keywords: Individual Patient Data; Health Assessment Questionnaire Score; Psoriasis Area Severity Index; Decision Uncertainty; Baseline Utility (search for similar items in EconPapers)
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