Presentation (CTI)

OBJECTIVES: The NICE highly specialised technology (HST) program evaluates new treatments for ultra rare diseases in England. Selecting appropriate outcome measures to capture the impact of the condition and benefits of the technology in clinical trials is challenging for rare conditions. This research aims to quantify the use of trial data to inform treatment effect and utility values in HST’s evaluated by NICE.
METHODS: Data was extracted from publicly available information on the NICE website for HST evaluations published between January 2020 and May 2025. This included pivotal clinical trial(s) outcomes and data sources for treatment response (for intervention and comparator) and utility values used in the original manufacturer’s economic model. The committee’s preferred source for treatment response and utilities was also collected.
RESULTS: Since May 2020, NICE has published guidance for 20 new technologies. Pivotal trial(s) partially or fully informed treatment response in the manufacturer’s model in 15 topics (75%) for the intervention and 8 topics (40%) for the comparator. 26 trials contributed data, including 11 (42%) single arm and 9 (35%) randomised controlled trials. Health related quality of life (HRQoL) data was collected for 13 technologies (65%) but used in manufacturer’s models for only 2 topics (10%; 15% of topics with trial HRQoL data). Reasons included lack of face validity or perceived insensitivity of current quality-of-life measures in capturing meaningful changes in the condition or important benefits to patients. Pivotal trials were preferred by committee for utilities in 4 of the 20 topics (20%; 31% of topics with trial HRQoL data).
CONCLUSIONS: This study highlights variation in using trial data for key model inputs in HSTs. Collecting relevant HRQoL data in rare conditions appears particularly challenging. For ultra rare diseases, careful consideration on the relevance of outcome measures should be taken at the clinical trial design phase.