Sequential Parallel Comparison Design for Assessing Induction, Maintenance, Long‐Term, and Other Treatment Effects on a Binary Endpoint

For a chronic disease, besides the treatment induction effect, it is also important to demonstrate the maintenance effect of long-term treatment use. To fulfill these and other objectives for a clinical study, we often apply one of three designs: the active treatment lead-in followed by randomized maintenance design, the randomized induction followed by re-randomized withdrawal maintenance design and the treat-through design (FDA 2022). Separately, a two-stage sequential parallel comparison design (SPCD) is frequently used in therapeutic areas where placebo has a large effect. In this paper, we use a SPCD for a clinical trial with a binary endpoint for induction, maintenance, long-term and other treatment effect assessments. This SPCD can actually be treated as a hybrid of the above three designs and has some additional advantages. For example, compared to the re-randomized withdrawal maintenance design, the SPCD does not need a re-randomization to simplify trial operation and it also provides controlled data for formal long-term efficacy and safety analyses. To fully utilize all available data of the two stages for an overall treatment effect evaluation, a weighted combination test is considered with the incorporation of correlations of the components. Further, a multiple imputation approach is applied to handle missing not at random data. Simulations are conducted to evaluate the performances of the methods and a data example is employed to illustrate the applications of the methods.