Published in:
01-12-2007 | Current Opinion
NICE Cost-Effectiveness Appraisal of Cholinesterase Inhibitors
Was the Right Question Posed? Were the Best Tools Used?
Published in: PharmacoEconomics | Issue 12/2007
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The National Institute for Health and Clinical Excellence (NICE) recently issued updated guidance on the use of cholinesterase inhibitors in the treatment of Alzheimer’s disease. NICE initially recommended that cholinesterase inhibitors no longer be used, but final guidance restricted treatment to patients with disease of a moderately severe stage. This decision was based largely on results from a heavily criticised economic evaluation that used an adaptation of the Assessment of Health Economics in Alzheimer’s Disease (AHEAD) model. As the developers of the AHEAD model, we examined the appropriateness of NICE’s economic analyses and presentation of results. We attempted to replicate NICE’s results by modifying the original AHEAD model. Sensitivity analyses were then run using the modified AHEAD model to evaluate the extent of uncertainty in predictions.
The AHEADNICE analyses resulted in an incremental cost-effectiveness ratio for galantamine of £82 000 per QALY gained (year 2003 values) from the perspective of the UK NHS and Personal Social Services. This was later revised to £46 000 per QALY, compared with <£9000 per discounted QALY gained (year 2001 values) in the original AHEAD model. Using our modified AHEAD with effectiveness estimates matching those of AHEADNICE, we show that NICE’s choice and presentation of sensitivity analyses obscured the instability of their estimates.
In the final NICE evaluation, the recommendation to delay treatment with cholinesterase inhibitors until patients have moderately severe disease was based on critical assumptions in the economic analyses that had little evidence to support them. The case of NICE’s guidance on cholinesterase inhibitors highlights the importance of transparent and valid economic evaluations and the dangers of using inappropriate modelling technologies, basing analyses on a limited subset of the available data, and insufficiently reflecting the uncertainty in estimates that are intended to inform decision makers.