Project Details
Abstract
Translational medicine is the “bench-to-beside” research which applies a basic laboratory discovery to
prevention, diagnosis, and individualized treatment of a certain disease. After completion of the Human
Genome Project (HGP), the disease biomarker can be identified. As a result, treatment modality for
predictive biomarker can be developed. However, the accuracy of diagnostic devices for identification of
such predictive biomarker is usually not perfect. Therefore, the treatment effects of the targeted therapy
estimated from predictive biomarker clinical trials could be biased. We will propose the method to
incorporate the inaccuracy of the diagnostic variance for statistical inference of the predictive biomarker
clinical trials under unselected design, with respect to the censored data. Hence, this research proposal will be
devoted to develop the statistical methodology for evaluation of following areas: (1) Statistical inference for
two types of designs under exponential distribution model. (2) Statistical inference for two types of designs
under exponential distribution model.
Project IDs
Project ID:PA10507-1180
External Project ID:MOST105-2118-M182-001
External Project ID:MOST105-2118-M182-001
Status | Finished |
---|---|
Effective start/end date | 01/08/16 → 31/07/17 |
Keywords
- Predictive biomarker
- Unselected design
- EM algorithm
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