DESCRIPTION (provided by applicant): The identification and evaluation of
interventions to reduce mortality and incidence of cancer is of critical public
interest. Practical tools for addressing some new and continuing challenges in
the design and analysis of clinical studies will be developed.
A major emphasis will be placed on the design for Phase 1-111 clinical trials.
The new developments will include strategies for early clinical studies of new
biologic agents, designs for single arm survival studies, and solutions to
several previously unresolved Phase III design issues. Flexible statistical
design software will also be developed.
New statistical methods for the joint analysis of longitudinal and time to
event data in the context of Phase III studies will be investigated. The
methods will take a Bayesian approach and utilize Markov Chain Monte Carlo
(MCMC) sampling algorithms.
There will be development and evaluation of exploratory survival analysis
methods. New algorithms for constructing and interpreting prognostic subgroups
of patients will be considered. Methodologies for model selection and for
combining covariates in clinical association studies of moderate dimensions
will also be investigated.
Other topics proposed arise directly from our collaborative work on clinical
trials. They will include analysis for time within a positive disease state and
methods for non-parametric covariate adjustment.
Collectively, the project will contribute to improvements in evaluating
efficacy of cancer therapies though better methods for design, conduct and
analysis of clinical studies.
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