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• W2536259224 abstract "Detecting meaningful change in clinical trials at early stages of drug development or for dementia prevention therapies is challenged by the insensitivity and variability of current measures. Changes in data capture methodology taking advantage of continuous home-based measurements of function using simple embedded sensors and devices provides an opportunity to improve the sensitivity and ecological validity of trials. Based on this principle a research platform (at The Oregon Center for Aging and Technology; ORCATECH) has been developed that employs pervasive computing technologies to harvest life's data in real time and show how using these data with high-frequency metrics that are reflective of tangible function may improve the conduct of trials. A total of 265 participants were enrolled beginning in 2007 in the Intelligent Systems for Assessing Aging Changes Study (ISAAC). Continuous data from subjects followed over 4 years are used as an example of this approach to show that these data allow us to collect enough data points to generate individual-specific distributions of functional outcomes such as computer usage and walking speed/variability within a short duration (e.g., 3 months). Using generalized mixed effects model, we estimated sample size needed to detect clinically meaningful reduction in longitudinal declines in functional outcomes. Sample sizes (or trial durations) required to achieve sufficient power to detect desired trial effects are significantly reduced using this approach in comparison with traditional clinical trial designs. For example, sample size estimates indicated approximately 2000 subjects with a follow-up duration of 4 years would be needed to achieve a 30% effect size when the outcome is an annually assessed memory test score. Using the metrics derived from our study, the required sample size can be reduced to lower than 100. Using individual-specific thresholds obtained from high-frequency in-home monitoring data that is focused on ecologically valid patient function provides an efficient alternative methodological trial paradigm. Future studies applying this method to various trial outcomes are warranted to validate the generalizability of this approach in clinical trials." @default.
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• W2536259224 date "2016-07-01" @default.
• W2536259224 modified "2023-09-27" @default.
• W2536259224 title "F1-04-04: Advancing Clinical Trials Using Real-Time, Ecologically Valid Data Capture Methodology" @default.
• W2536259224 doi "https://doi.org/10.1016/j.jalz.2016.06.286" @default.
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