Exploring a Patient-Centered 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 EQ-5D utility data, the National Institute for Health and Care Excellence recommends sourcing utility values from a proxy health condition, provided that data indicate that the health-related quality of life (HRQoL) impact of the conditions is similar. Given that there is no standard practice for identifying proxy conditions, this study presents a patient-centered 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 conditions similar to AA with overlapping HRQoL domains. 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, it was selected as the proxy condition. Conceptual models indicated that both conditions affected patients’ physical, emotional, and functional well-being. 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 study presents a potential approach to identify proxy conditions for diseases that may be underrepresented in terms of HRQoL data.