There is growing interest in the design and implementation of cancer prevention trials. The key idea is to have agents which interfere with carcinogenesis and/or the preclinical stage. In this article we develop multi-stage stochastic models for the planning of cancer prevention trials. For known inputs it is possible to calculate the incidence of disease for the control and intervention groups. Consequently we find designs that balance the required sample size and follow-up time while guaranteeing prespecified error probabilities. Moreover such models can incorporate the mode of action of the intervention as well as compliance. The model has been applied to breast cancer to determine the implications for planning breast cancer intervention trials. Although the model addresses issues in cancer prevention, it is quite general and may be suitable for other chronic diseases. Copyright (C) 2000 John Wiley and Sons, Ltd.
|Number of pages||13|
|Journal||Statistics in Medicine|
|State||Published - 15 Aug 2000|
ASJC Scopus subject areas
- Statistics and Probability