Added value of amyloid PET in individualized risk predictions for MCI patients

Introduction To construct a prognostic model based on amyloid positron emission tomography (PET) to predict clinical progression in individual patients with mild cognitive impairment (MCI). Methods We included 411 MCI patients from the Alzheimer's Disease Neuroimaging Initiative. Prognostic models were constructed with Cox regression with demographics, magnetic resonance imaging, and/or amyloid PET to predict progression to Alzheimer's disease dementia. The models were validated in the Amsterdam Dementia Cohort. Results The combined model (Harrell's C = 0.82 [0.78–0.86]) was significantly superior to demographics (β = 0.100, P < .001), magnetic resonance imaging (β = 0.037, P = .011), and PET only models (β = 0.053, P = .003).The models can be used to calculate individualized risk, for example, a female MCI patient (age = 60, APOE ε4 positive, Mini‐Mental State Examination = 25, hippocampal volume = 5.8 cm 3 , amyloid PET positive) has 35% (19–57) risk in one year and 85% (64–97) risk in three years. Model performances in the Amsterdam Dementia Cohort were reasonable. Discussion The present study facilitates the interpretation of an amyloid PET result in the context of a patient's own characteristics and clinical assessment.