Forecasting individual progression trajectories in Alzheimer's disease.

ABSTRACT: The anticipation of progression of Alzheimer's disease (AD) is crucial for evaluations of secondary prevention measures thought to modify the disease trajectory. However, it is difficult to forecast the natural progression of AD, notably because several functions decline at different ages and different rates in different patients. We evaluate here AD Course Map, a statistical model predicting the progression of neuropsychological assessments and imaging biomarkers for a patient from current medical and radiological data at early disease stages. We tested the method on more than 96,000 cases, with a pool of more than 4,600 patients from four continents. We measured the accuracy of the method for selecting participants displaying a progression of clinical endpoints during a hypothetical tria

SUBMITTER: Maheux E 

PROVIDER: S-EPMC9918533 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature