A Machine Learning Approach to Predict Cognitive Decline in Alzheimer Disease Clinical Trials

BACKGROUND AND OBJECTIVES: Among the participants of Alzheimer disease (AD) treatment trials, 40% do not show cognitive decline over 80 weeks of follow-up. Identifying and excluding these individuals can increase power to detect treatment effects. We aimed to develop machine learning-based predictive models to identify persons unlikely to show decline on placebo treatment over 80 weeks. METHODS: . DISCUSSION: Our results indicate that predictive models have the potential to improve the design of AD trials through selective inclusion and exclusion criteria based on expected cognitive decline. Such predictive models need further validation across data from different AD clinical trials.