Innovative Clinical Trial Design and Analysis (Grant Cycle 1)

 

Design is a crucial first step in clinical trials. Well-designed studies are essential for successful cancer research and cancer drug development. Innovative clinical trial designs can potentially require fewer patients, save resources, and accelerate cancer drug development. Although much effort has been put into analysis methods with complicated data structures, the design aspect has not kept pace. Hence developing statistical methods for innovative clinical trial design is timely and much needed.

In this project, we propose to develop new statistical methodology to address issues in the design and analysis of clinical trials. We will investigate both the analytical and the empirical behavior of the proposed methodologies. Related software will be developed. These high impact and innovative statistical methods will improve public health by enabling accurate and efficient estimation of sample size and power for studies with time-to-event and longitudinal endpoints, cluster randomized cancer prevention and therapeutic trials, and cancer drug development trials. The specific aims are:

Aim 1: Develop methods for design and sample size calculation for longitudinal and joint models for longitudinal and survival data.

Aim 2: Develop statistical methodology for the design and analysis of group randomized cancer prevention trials with survival and recurrent event outcomes.

Aim 3: Develop statistical methodology for cancer drug development through the following three sub-aims:

i:	Develop methods for the design and analysis of clinical trials of targeted therapy.
ii:	Develop designs for phase II trials that are predictive of phase III trial success.
iii:	Develop methods for the design and analysis of partially randomized clinical trials.