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Knowledge of longitudinal progression in mild Alzheimer’s disease (AD) is required for the evaluation of disease-modifying therapies. Our aim was to observe the effects of long-term cholinesterase inhibitor (ChEI) therapy in mild AD patients in a routine clinical setting.    Methods  This was a prospective, open-label, non-randomized, multicenter study of ChEI treatment (donepezil, rivastigmine or galantamine) conducted during clinical practice. The 734 mild AD patients (Mini-Mental State Examination (MMSE) score 20 to 26) were assessed at baseline and then semi-annually over three years. Outcome measures included the MMSE, Alzheimer’s Disease Assessment Scale-cognitive subscale (ADAS-cog), Clinician’s Interview-Based Impression of Change (CIBIC) and Instrumental Activities of Daily Living (IADL) scale.    Results  After three years of ChEI therapy, 31% (MMSE) and 33% (ADAS-cog) of the patients showed improved/unchanged cognitive ability, 33% showed improved/unchanged global performance and 14% showed improved/unchanged IADL capacity. Higher mean dose of ChEI and lower educational level were both predictors of more positive longitudinal cognitive and functional outcomes. Older participants and those with a better IADL score at baseline exhibited a slower rate of cognitive decline, whereas younger participants and those with higher cognitive status showed more preserved IADL ability over time. Gender and apolipoprotein E (APOE) genotype showed inconsistent results. Prediction models using the abovementioned scales are presented.    Conclusions  In naturalistic mild AD patients, a marked deterioration in IADL compared with cognitive and global long-term outcomes was observed, indicating the importance of functional assessments during the early stages of the disease. The participants’ time on ChEI treatment before inclusion in studies of new therapies might affect their rate of decline and thus the comparisons of changes in scores between various studies. An increased understanding of expected disease progression in different domains and potential predictors of disease progression is essential for assessment of future therapies in AD.

Progression of mild Alzheimer’s disease: knowledge and prediction models required for future treatment strategies