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

Abstract

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 cm³, 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.

Keywords: Alzheimer's disease; Amyloid positron emission tomography; Biomarkers; MCI; Progression.

Fig. 1

Probability isographs for three-year progression to AD-dementia; Probability of progression within three years based on the combined model. Risk is low (green-yellow) in amyloid PET negative patients. Risk increases with lower HCV, younger age, and lower MMSE. In this combined model, amyloid PET clearly has the strongest contribution to prognosis as high probabilities can be found in amyloid PET positive patients (orange-red).