Predicting Conversions from Normal to MCI and from MCI to AD with Clinical Variables in the National Alzheimer’s Coordinating Center Uniform Data Set Version 3: Application of Big Data Analytics and Transition Probability Calculators

Clinical trials are increasingly focused on pre‐manifest and early Alzheimer’s disease (AD). Accurately predicting those who transit from normal to MCI or from MCI to dementia/AD (true positives) versus non‐progressors (false positives) is challenging. Biomarker positivity and comorbidity information are often not sufficient to identify those who are destined to have symptom progressions. Accurate identification of progressors is important to avoid un‐necessary treatment as well as to improve trial efficiency.