All ETDs from UAB

Advisory Committee Chair

Gary R Cutter

Advisory Committee Members

Richard E Kennedy

Lon S Schneider

Alfred A Bartolucci

Inmaculada B Aban

Document Type


Date of Award


Degree Name by School

Doctor of Philosophy (PhD) School of Public Health


The goal of this dissertation is to investigate the effect of novel clinical trial designs for Alzheimer's disease (AD), and to provide applications for their use in real trials. The data used for our simulation is a meta-data base of completed trials. In the first paper, we investigate the sample size re-estimation (SSR) adaptive design based on the effect size and the variance without taking into account the longitudinal feature of the trials. In the second paper, we take advantage of that feature to explore the SSR based on the variance of the rate of change in the longitudinal measurements. Finally, in the third paper, we extend the delayed-start (DS) design to AD by proposing some of the crucial design parameters. We also investigate the power of the DS design, and compare it to the power of the typical randomized parallel-group design. Through our simulations, we discover that SSR based on the effect size or the variance without taking into account of the longitudinal feature of the trial can be effective for trials with small or moderate initial sample sizes. However, when the initial sample size is over 200, the gain in power after SSR is no longer significant. After incorporating the longitudinal feature, we show that SSR based on the rate of change is not only effective, but also allows the luxury to adapt the sample into two ways: increase the number of recruits or add the number of measurements. However, increasing the number of recruits is more likely. Finally, for the DS design, we prove that the optimal sample size allocation ratio is 1:1:1; the optimal weight has a simple formula; the correlation between slopes can be negative and positive; and the optimal treatment-switch point is the middle point or the second one of the middle two.

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