Designing cancer prevention trials: a stochastic model approach

There is growing interest in the design and implementation of cancer preven tion trials. The key idea is to have agents which interfere with carcinogen esis and/or the preclinical stage. In this article we develop multi-stage s tochastic models for the planning of cancer prevention trials. For known in puts it is possible to calculate the incidence of disease for the control a nd intervention groups. Consequently we find designs that balance the requi red sample size and follow-up time while guaranteeing prespecified error pr obabilities. Moreover such models can incorporate the mode of action of the intervention as well as compliance. The model has been applied to breast c ancer to determine the implications for planning breast cancer intervention trials. Although the model addresses issues in cancer prevention, it is qu ite general and may be suitable for other chronic diseases. Copyright (C) 2 000 John Wiley & Sons, Ltd.