INDIRECT TREATMENT COMPARISONS IN UK HTA: WHEN ARE THEY ACCEPTED AND HOW DO THEY SHAPE VALUE PERCEPTIONS?
Author(s)
Priya Toor, Biochemistry BSc, Health Economics MSc.
Lightning Health, London, United Kingdom.
Lightning Health, London, United Kingdom.
OBJECTIVES: Head-to-head trials are often infeasible in orphan and oncology indications due to factors such as small patient populations and ethical considerations. As a result, indirect treatment comparisons (ITCs) can be the only source of comparative evidence in National Institute for Health and Care Excellence (NICE) technology appraisals. However, the acceptability of ITCs is assessed on a case-by-case basis, and their overall acceptance remains limited.This research examines the use of ITCs in NICE appraisals of orphan and oncology therapies, explores factors associated with their acceptance or rejection, and assesses their impact on value perceptions and reimbursement decision-making.
METHODS: A targeted review of UK NICE technology appraisals (7-12) and highly specialised technology evaluations (2-5) published between 2020 and 2025 was undertaken, focusing on orphan-designated products and oncology indications.
RESULTS: ITC acceptance was more likely when the condition carried high severity, existing treatments were suboptimal and the ITC was anchored or supported by real-world evidence. Where an anchored network meta-analysis (NMA) could be constructed through a connected evidence network, committees were generally willing to accept uncertainty and issue positive recommendations, even where heterogeneity was acknowledged. Rejection was predominantly driven by methodological concerns, particularly submissions relying on unanchored matching-adjusted indirect comparisons (MAICs) with small sample sizes, insufficient covariate adjustment, or uncertain survival extrapolations, which were frequently considered insufficiently robust to support decision-making. In some cases, ITC evidence facilitated reimbursement in subpopulations that may not have gained access otherwise.
CONCLUSIONS: ITCs can meaningfully inform NICE decision-making, but their influence is highly conditional. Acceptance is most likely in particularly severe or rare conditions, where direct evidence is unavailable and appraisal committees are willing to tolerate uncertainty. Anchored and methodologically robust approaches can shape value assessments and support positive recommendations.
METHODS: A targeted review of UK NICE technology appraisals (7-12) and highly specialised technology evaluations (2-5) published between 2020 and 2025 was undertaken, focusing on orphan-designated products and oncology indications.
RESULTS: ITC acceptance was more likely when the condition carried high severity, existing treatments were suboptimal and the ITC was anchored or supported by real-world evidence. Where an anchored network meta-analysis (NMA) could be constructed through a connected evidence network, committees were generally willing to accept uncertainty and issue positive recommendations, even where heterogeneity was acknowledged. Rejection was predominantly driven by methodological concerns, particularly submissions relying on unanchored matching-adjusted indirect comparisons (MAICs) with small sample sizes, insufficient covariate adjustment, or uncertain survival extrapolations, which were frequently considered insufficiently robust to support decision-making. In some cases, ITC evidence facilitated reimbursement in subpopulations that may not have gained access otherwise.
CONCLUSIONS: ITCs can meaningfully inform NICE decision-making, but their influence is highly conditional. Acceptance is most likely in particularly severe or rare conditions, where direct evidence is unavailable and appraisal committees are willing to tolerate uncertainty. Anchored and methodologically robust approaches can shape value assessments and support positive recommendations.
Conference/Value in Health Info
2026-11, ISPOR Europe 2026, Vienna, Austria
Value in Health, Volume 29, Issue 12S
Code
HTA105
Topic
Health Technology Assessment
Topic Subcategory
Decision & Deliberative Processes
Disease
Oncology