P4-318: evidence for age-associated cognitive decline in a large database of lumosity internet game scores

A significant obstacle to developing effective treatments for Alzheimer's disease (AD) is the cost of clinical trials. Valid internet-based neuropsychological tests may reduce the costs to longitudinally assess cognitively normal subjects who are at risk for cognitive decline and to recruit these subjects into AD prevention trials. Memory Match (LMM) is an online working memory game developed by Lumos Labs. Although the validity of LMM scores as measures of working memory has not yet been evaluated, longitudinal trends in LMM scores may indicate declining performance due to aging or disease. LMM learning rates, forgetting rates, and changes in the learning rates over time can be estimated before subjects are enrolled in randomized studies and used to predict decline, thus increasing statistical power, reducing sample sizes, and lowering costs. With data provided by Lumos Labs, the effects of age and time on learning and forgetting rates were estimated with a mixed effects linear regression model. 2,212 Lumosity users (ages, 40 - 79) played forty LMM game sessions following ten run-in sessions for > 1 year. Sample sizes were calculated for 80% power to detect slowing the rate of decline in the learning rate by 25% in 1 year trials for subjects selected from the lowest quartile of learning rate change estimates (decliners). There were significant effects of age on lower initial LMM scores (β = -.39, P < .0001), lower initial learning rates (β = -.0031, P < .0001) and greater declines in learning rates over time (β = -8.00E-06, P < .001). Sample sizes as small as 136 subjects/arm were estimated for 1-year trials using subjects in the lower quartile of learning rate decline. The data suggest that declining learning rates are associated with older ages and that recruiting subjects in the lower quartile of learning rate decline significantly increases the statistical power to detect a treatment effect in clinical trials. As such, our data support the potential use of online memory games to identify subjects at risk for cognitive decline with smaller sample sizes and lower cost than traditional recruitment methods.