OBJECTIVES: Alzheimer’s disease (AD) is a progressive neurological disease, characterised by deterioration in patient cognition, function and behaviour. No disease-modifying treatments are currently approved for use in the UK, with current practice focused on symptom management. This analysis aimed to identify cost-effective treatment profiles for a hypothetical emerging treatment (HET) in patients with mild AD from an English NHS perspective.

METHODS: A lifetime Markov model was developed to estimate costs and health outcomes for patients with AD treated with current standard of care (donepezil and memantine) versus a HET. The model structure was based on the Institute for Clinical and Economic Review (ICER) evidence review for aducanumab, with five health states characterising the severity of AD (mild cognitive impairment (MCI) due to AD, mild AD, moderate AD, severe AD, and death). Setting of care (community or long-term care) was also tracked. Treatment was assumed to slow disease progression, modelled via a hazard ratio (HR). Clinical data, cost (direct medical) and utility inputs were obtained from the literature and UK data sources. Two-way sensitivity analysis was used to explore cost-effective treatment profiles, and one-way sensitivity analysis was used to determine drivers of cost effectiveness.

RESULTS: For an emerging treatment with HRs on progression of 0.9, 0.7, and 0.5, the maximum annual treatment cost at a willingness-to-pay threshold of £30,000 was £825, £2,550, and £4,400, respectively. The drivers of cost effectiveness were treatment efficacy, annual treatment cost, inclusion of social care costs, and utility values.

CONCLUSIONS: Using established AD modelling approaches, a range of cost-effective profiles were identified for a HET. The analysis suggests that a commercial arrangement would likely be required for a HET to be considered cost-effective from an English NHS perspective. Drivers of cost effectiveness in this AD analysis were found to be consistent with those detailed in literature.