Adaptive group sequential test for clinical trials with changing patient population.

In clinical trials, a standard group sequential test with a fixed number of planned interim analyses is usually considered to assess the effect of a test treatment under study. The standard group sequential test is statistically valid under the assumption that the patient population remains unchanged from one interim analysis to another. In practice, however, this assumption is often not met because the trial may be modified after the review of the clinical data at interim. As a result, the original patient population may have changed to a similar but different patient population. In this paper, we consider changes in patient population related to some covariates of an on-going trial through a linear regression model. Under this model, we can make inference on the original target population based on additional data from the changed populations. A new group sequential test procedure that accounts for the effect of population changes is proposed. A simulation was performed to evaluate the performance of the proposed method. The results indicate that the type I error rate of the proposed test procedure is well preserved, while the type I error rate of the standard group sequential test is inflated as the population changes. Statistical powers of the proposed group sequential test are also presented.

Duke Scholars

Author Shein-Chung Chow Biostatistics & Bioinformatics, Division of Biostatistics