Estimating Treatment Effect for Target Population in Psychiatric Clinical Trials Using Placebo Lead-in Design

The placebo lead-in design is commonly utilized in psychiatric clinical trials to mitigate high placebo response rates; conventional methods for estimating treatment effects typically rely solely on data from the second period, disregarding the enrichment process integral to this design. This limitation can result in an incomplete assessment of the true treatment effect in the intended target population, as desired in real-world clinical settings. To overcome this limitation, a novel adjusted estimator is proposed, leveraging the probability structure of the placebo lead-in design to provide a more accurate estimation of the treatment effect for the target population. When a treatment effect exists, the traditional estimator often tends to overestimate the effect. In contrast, the adjusted estimator delivers a more reliable estimate, particularly when the proportion of non-responders during the placebo lead-in period is sufficiently high (e.g., above 70%). A case study is included to illustrate the analysis approach and result interpretation. Furthermore, actionable recommendations are provided to support the effective implementation of the placebo lead-in design.