A simple test for the treatment effect in clinical trials with a sequential parallel comparison design and negative binomial outcomes

In placebo‐controlled, double‐blinded, randomized clinical trials, the presence of placebo responders reduces the effect size for comparison of the active drug group with the placebo group. An attempt to resolve this problem is to use the sequential parallel comparison design (SPCD). Although there are SPCDs with dichotomous or continuous outcomes, an SPCD with negative binomial outcomes—with which investigators deal eg, in clinical trials involving multiple sclerosis, where the investigators are still concerned about the presence of placebo responders—has not yet been discussed. In this article, we propose a simple test for the treatment effect in clinical trials with an SPCD and negative binomial outcomes. Through simulations, we show that the analysis method achieves the nominal type I error rate and power, whereas the sample size calculation provides the sample size with adequate power accuracy.     

Sequential parallel comparison design with two coprimary endpoints

A placebo‐controlled randomized clinical trial is required to demonstrate that an experimental treatment is superior to its corresponding placebo on multiple coprimary endpoints. This is particularly true in the field of neurology. In fact, clinical trials for neurological disorders need to show the superiority of an experimental treatment over a placebo in two coprimary endpoints. Unfortunately, these trials often fail to detect a true treatment effect for the experimental treatment versus the placebo owing to an unexpectedly high placebo response rate. Sequential parallel comparison design (SPCD) can be used to address this problem. However, the SPCD has not yet been discussed in relation to clinical trials with coprimary endpoints. In this article, our aim was to develop a hypothesis‐testing method and a method for calculating the corresponding sample size for the SPCD with two coprimary endpoints. In a simulation, we show that the proposed hypothesis‐testing method achieves the nominal type I error rate and power and that the proposed sample size calculation method has adequate power accuracy. In addition, the usefulness of our methods is confirmed by returning to an SPCD trial with a single primary endpoint of Alzheimer disease‐related agitation.