FROM HEALTH TECHNOLOGY ASSESSMENT TO CLINICAL GUIDELINES: APPLICABILITY OF THE NICE SEVERITY MODIFIER
Author(s)
Arianna Gentilini, PhD1, Claire Hawksworth, MSc2, Bhash Naidoo, PhD1, Peter Roche, MSc1, Eric Slade, MSc3, Nichole Taske, PhD1.
1NICE, London, United Kingdom, 2NICE, Manchester, United Kingdom, 3Health Economics Advisor, NICE, London, United Kingdom.
1NICE, London, United Kingdom, 2NICE, Manchester, United Kingdom, 3Health Economics Advisor, NICE, London, United Kingdom.
OBJECTIVES: NICE applies a severity modifier (SM) in its technology appraisal (TA) programme, weighting incremental QALYs by ×1.2 or ×1.7 according to absolute (AS) and proportional (PS) lifetime QALY shortfall versus an age/sex-matched general population. With NICE’s move to a dynamic assessment, there is a need to harmonise its methods across its programmes. To support with this objective, we assessed how often, and how readily, this TA-derived SM could be applied to NICE guidelines.
METHODS: To estimate how often the SM would be applied in guidelines, three different complementary analyses were undertaken covering guidelines published or updated from 2022. (1) For a random sample of 15 guidelines, AS and PS were calculated for decision problems with a CUA reporting mean age, sex distribution and standard of care (SoC) QALYs; (2) the proportion of guidelines including a CUA was estimated from NICE's economic-modelling repository; and (3) a purposive disease-mapping exercise (cancer guidelines, guidelines incorporating TAs, GenAI-flagged topics) recorded overlap with diseases that have qualified for an SM in a TA.
RESULTS: Only half of recent guidelines included a CUA (51/98; 52%). Across sampled guideline decision problems, the SM was rarely calculable and, when it was, was not triggered in any in-scope decision problem. Disease mapping showed limited overlap with SM-qualifying populations (5/98), primarily oncology. Where overlap existed, differences in disease stage, population definition, and SoC assumptions often prevented SM application.
CONCLUSIONS: Applying the SM in guidelines is methodologically constrained. SoC QALYs are often not quantifiable and short time horizons make lifetime extrapolation difficult, raising equity concerns where severity cannot be formally captured. This exploratory analysis highlights broader conceptual questions, including how to account for heterogeneous and comorbid populations, preventive interventions, diagnostic and public-health decision problems. Refinement, such as determining societal preferences for valuing severity, would also help to support application of SM beyond HTA assessment.
METHODS: To estimate how often the SM would be applied in guidelines, three different complementary analyses were undertaken covering guidelines published or updated from 2022. (1) For a random sample of 15 guidelines, AS and PS were calculated for decision problems with a CUA reporting mean age, sex distribution and standard of care (SoC) QALYs; (2) the proportion of guidelines including a CUA was estimated from NICE's economic-modelling repository; and (3) a purposive disease-mapping exercise (cancer guidelines, guidelines incorporating TAs, GenAI-flagged topics) recorded overlap with diseases that have qualified for an SM in a TA.
RESULTS: Only half of recent guidelines included a CUA (51/98; 52%). Across sampled guideline decision problems, the SM was rarely calculable and, when it was, was not triggered in any in-scope decision problem. Disease mapping showed limited overlap with SM-qualifying populations (5/98), primarily oncology. Where overlap existed, differences in disease stage, population definition, and SoC assumptions often prevented SM application.
CONCLUSIONS: Applying the SM in guidelines is methodologically constrained. SoC QALYs are often not quantifiable and short time horizons make lifetime extrapolation difficult, raising equity concerns where severity cannot be formally captured. This exploratory analysis highlights broader conceptual questions, including how to account for heterogeneous and comorbid populations, preventive interventions, diagnostic and public-health decision problems. Refinement, such as determining societal preferences for valuing severity, would also help to support application of SM beyond HTA assessment.
Conference/Value in Health Info
2026-11, ISPOR Europe 2026, Vienna, Austria
Value in Health, Volume 29, Issue 12S
Code
HTA216
Topic
Economic Evaluation, Health Technology Assessment, Methodological & Statistical Research
Topic Subcategory
Decision & Deliberative Processes, Value Frameworks & Dossier Format
Disease
No Additional Disease & Conditions/Specialized Treatment Areas