The main goal of Phase II cancer clinical trials is to identify the therapeutic efficacy of new treatments. For ethical reasons, group sequential procedures, which allow for early stopping when a treatment is either extremely effective or extremely ineffective, have been widely employed in these trials. Although several useful design methods have been discussed in the literature (Fleming, 1982, Biometrics 38, 143-152; Lee, 1979, Cancer Treatment Reports 63, No. 11-12), we are unaware of any results addressing the problem of finding an optimal rule easily by computer. In this paper, using an idea based on the Neyman-Pearson lemma, we propose a method to search over a restricted set of designs and to select the optimal one in this set according to optimality criteria. In all the combinations we have investigated (more than 100) the optimal design produced by our method is the true global optimum. Other applications are discussed.
ASJC Scopus subject areas
- Statistics and Probability
- Biochemistry, Genetics and Molecular Biology(all)
- Immunology and Microbiology(all)
- Agricultural and Biological Sciences(all)
- Applied Mathematics