The Role of Condition-Specific Preference-Based Measures in Health Technology Assessment

Abstract

A condition-specific preference-based measure (CSPBM) is a measure of health-related quality of life (HRQOL) that is specific to a certain condition or disease and that can be used to obtain the quality adjustment weight of the quality-adjusted life-year (QALY) for use in economic models. This article provides an overview of the role and the development of CSPBMs, and presents a description of existing CSPBMs in the literature. The article also provides an overview of the psychometric properties of CSPBMs in comparison with generic preference-based measures (generic PBMs), and considers the advantages and disadvantages of CSPBMs in comparison with generic PBMs. CSPBMs typically include dimensions that are important for that condition but may not be important across all patient groups. There are a large number of CSPBMs across a wide range of conditions, and these vary from covering a wide range of dimensions to more symptomatic or uni-dimensional measures. Psychometric evidence is limited but suggests that CSPBMs offer an advantage in more accurate measurement of milder health states. The mean change and standard deviation can differ for CSPBMs and generic PBMs, and this may impact on incremental cost-effectiveness ratios. CSPBMs have a useful role in HTA where a generic PBM is not appropriate, sensitive or responsive. However, due to issues of comparability across different patient groups and interventions, their usage in health technology assessment is often limited to conditions where it is inappropriate to use a generic PBM or sensitivity analyses.

U.K. utility weights for the EORTC QLU‐C10D

“…The role of condition‐specific PBMs such as the EORTC QLU‐C10D is debated by health economists (see, e.g., Brazier et al, ; Versteegh, Leunis, Uyl‐De Groot, & Stolk, ). For use in health technology assessments undertaken to inform resource allocation decisions, their use is often limited to conditions where a generic PBM is not appropriate, sensitive, or responsive, or for use in sensitivity analyses (Rowen et al, ). This is for reasons of comparability, where health technology assessment is used to inform the allocation of resources across interventions, conditions, and populations, and the NICE, in particular, recommend EQ‐5D in their reference case (NICE, ).…”

“…PBMs can either be developed de novo or by adapting pre‐existing health‐related quality of life (HRQoL) profile measures (Brazier et al, ; Rowen, Brazier, Ara, & Azzabi Zouraq, ). The advantage of the latter approach is that it means that utility weights can be derived using data that are already collected using an existing measure without additional respondent burden.…”

Special Edition on Utility Measurement, PharmacoEconomics

“…For example, the paper on international guidelines is very useful because these issues can change quite quickly [1]. The current conclusions on the role of different types of measures is also an important update [2,3].…”

“…One interesting general conclusion is that the generic PBMs remain in a dominant position as choice of outcome measure [2]. The team conclude that condition-specific PBMs have a role to play where there is good evidence that generic measures are not able to measure changes in health [2].…”

“…The team conclude that condition-specific PBMs have a role to play where there is good evidence that generic measures are not able to measure changes in health [2]. If there is no evidence for insensitivity in generic measures then the results from the condition-specific measure should be limited to sensitivity analyses (in a decision model).…”