Crossover designs have some advantages over standard clinical trial designs and they are often used in trials evaluating the efficacy of treatments for infertility. However, clinical trials of infertility treatments violate a fundamental condition of crossover designs, because women who become pregnant in the first treatment period are not treated in the second period. In previous research, to deal with this problem, some new designs, such as re-randomization designs, and analysis methods including the logistic mixture model and the beta-binomial mixture model were proposed. Although the performance of these designs and methods has previously been evaluated in large-scale clinical trials with sample sizes of more than 1000 per group, the actual sample sizes of infertility treatment trials are usually around 100 per group. The most appropriate design and analysis for these moderate-scale clinical trials are currently unclear. In this study, we conducted simulation studies to determine the appropriate design and analysis method of moderate-scale clinical trials for irreversible endpoints by evaluating the statistical power and bias in the treatment effect estimates. The Mantel-Haenszel method had similar power and bias to the logistic mixture model. The crossover designs had the highest power and the smallest bias. We recommend using a combination of the crossover design and the Mantel-Haenszel method for two-period, two-treatment clinical trials with irreversible endpoints.
Keywords: crossover designs; irreversible endpoints; re-randomization designs; the Mantel-Haenszel method; the logistic mixture model.
Copyright © 2015 John Wiley & Sons, Ltd.