SELECTION DESIGNS FOR PILOT-STUDIES BASED ON SURVIVAL

In cancer clinical trials new regimens are typically tested for antitu mor activities in patients with advanced disease. The promising ones a re then compared to the standard treatment in a randomized study, some times performed on patients with earlier-stage disease. When there are multiple promising regimens, it may not be possible to compare all of them to the control group because of the prohibitive sample size and study length requirements. We propose a design that uses the Cox regre ssion model to select a best treatment based on survival before the ra ndomized comparison. Sample sizes for an asymptotically correct select ion probability of .90 are presented for Weibull survival distribution s with parameters in a range we consider to be of practical interest. Simulations verify that the asymptotic approximations to the correct s election probabilities are quite satisfactory. Simulations also indica te that the procedure is reasonably robust to the proportional hazards assumption. In contrast to the two-stage screening design recommended by Schaid, Wieand, and Therneau (1990, Biometrika 77, 507-513), our d esign has the advantage of fitting naturally to a progression of cance r trials where the selection and comparison phases are carried out on different populations of patients. When the population of interest sta ys the same, our design can be more conservative on the average but of fers the opportunity to base the comparative trial on the experience g ained during the selection phase.