Exploring a patient-centred methodology to identify suitable proxy conditions as a source for utility data, using alopecia areata as a case example.

Abstract

Objectives: In the absence of EuroQol 5-dimension (EQ-5D) utility data, the National Institute for Health and Care Excellence (NICE) recommend sourcing utility values from a proxy health condition, provided data indicate that the health-related quality of life (HRQoL) impact of the conditions is similar. Given there is no standard practice for identifying proxy conditions, this study presents a patient-centred approach for selecting a proxy condition, using alopecia areata (AA) as an example.

Methods: A structured electronic search was conducted to identify conceptual models for similar conditions with overlapping HRQoL domains with AA. Conceptual models were compared to determine the most suitable proxy condition, defined as the condition with the most overlapping domains and reported similarities between patient HRQoL. A search and comparison of utility data between AA and the selected proxy condition was conducted to validate their comparability in HRQoL impact.

Results: Seven conditions with overlapping HRQoL domains with AA were identified using conceptual models. Atopic dermatitis (AD) had the most overlapping domains (n = 6) and the greatest evidence of similarities between patient HRQoL, thus was selected as the proxy condition. Conceptual models indicated that both conditions affect patients' physical, emotional, and functional wellbeing. Furthermore, AD and AA utilities were comparable, supporting the choice of AD as the proxy condition.

Conclusions: Given the correlation observed between AA and the selected proxy condition using this methodology, this research has presented a potential approach to identify proxy conditions for diseases which may be underrepresented in terms of HRQoL data.