Disease progression and costs of care in Alzheimer's disease patients treated with donepezil: a longitudinal naturalistic cohort

Background/Aims Improved data and methods are needed for modeling disease progression in Alzheimer's disease (AD) for economic evaluation of treatments. The aim is to estimate prediction models for long-term AD progression and subsequently economic outcomes. Methods Three-year follow-up data on 435 patients treated with the cholinesterase inhibitor donepezil in clinical practise were analyzed. Regression models were estimated for long-term prediction of decline in cognitive function (ADAS-cog) and activities in daily living (ADL) ability, risk of institutionalization and costs of care. Results The cognitive deterioration was estimated at between 1.6 and 4 ADAS-cog points per every 6 months, increasing with disease severity. Cognitive function was an important predictor of ADL-ability, which itself was the most important predictor of the risk of institutionalization and costs of care. Combining all models in a cross-validation process generated accurate predictions of costs of care at each 6 months follow-up. Conclusion The proposed methods for representing AD progression and economic outcomes can be used in microsimulation models for the economic evaluation of new treatments.