Properties of adaptive clinical trial signature design in the presence of gene and gene-treatment interaction

Traditional phase III clinical trials are powered to detect an overall treatment effect. However, it has increasingly been shown that many treatments are effective only for a subset of a population. The adaptive signature design uses genomic/proteomic information to prospectively predict a subset of...

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Bibliographic Details
Published in:Communications in statistics. Simulation and computation 2017-11, Vol.46 (10), p.8233-8250
Main Authors: Cambon, A. C., Baumgartner, K. B., Brock, G. N., Cooper, N. G. F., Wu, D., Rai, S. N.
Format: Article
Language:English
Subjects:
Adaptive signature design
classification
Clinical trials
Computer simulation
dimension reduction
interaction
machine learning
Mathematical models
Medical research
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Summary:Traditional phase III clinical trials are powered to detect an overall treatment effect. However, it has increasingly been shown that many treatments are effective only for a subset of a population. The adaptive signature design uses genomic/proteomic information to prospectively predict a subset of patients more sensitive to treatment. Tests for overall treatment effect and for treatment effect in the predicted subset are conducted. In this work properties of the adaptive signature design are investigated through simulation. It was found that models which excluded expression main effect terms had higher empirical power than models which included them.
ISSN:0361-0918
1532-4141
DOI:10.1080/03610918.2016.1275690