Presentation (CTI)

OBJECTIVES: In rare diseases, the collection of robust health-related quality of life (HRQoL) data is often challenging due to small and geographically dispersed patient populations. Furthermore, many rare diseases involve cognitive impairment or complex symptom profiles, limiting the feasibility and validity of preference-based instruments and necessitating the use of proxy or vignette-based approaches. The objective of this study was to examine how health state utilities have been sourced or estimated for rare diseases when conventional utility data are limited or unavailable in National Institute for Health and Care Excellence (NICE) technology appraisals (TAs) and highly specialised technologies (HSTs). This included assessing the extent to which different approaches were accepted or critiqued, and identifying factors influencing preferred methods.
METHODS: TAs and HSTs published in the last 10 years (June 2016 to mid-June 2026) were reviewed. Only appraisals of rare diseases, defined according to the European Medicines Agency (EMA) orphan designation criteria were included. Rare oncology, haematological, and immunological conditions were excluded. Withdrawn or terminated appraisals were not considered. Committee papers were reviewed, and approaches used to estimate patient HRQoL were further analysed.
RESULTS: A total of 48 appraisals were selected, of which 22 were TAs and 26 were HSTs. In general, the number of appraisals between 2016 and 2026 increased over the years, with the lowest number assessed in 2018 and 2020 (n=1) and the highest in 2023 (n=10). Trial-based utility data were available in most TAs, whereas HSTs more frequently relied on alternative approaches due to limited data availability.
CONCLUSIONS: In rare disease NICE appraisals, limitations in HRQoL data necessitate the use of diverse utility estimation approaches. The acceptability of these approaches depends on the availability of supporting evidence and the extent to which they are validated and triangulated. These findings highlight the need for greater methodological guidance on utility estimation in rare diseases.