On Treatment Effect in Sequential Parallel Comparison Design

• Activity Number: 29 - Statistical Issues Specific to Therapeutic Areas, Power and Sample Size Calculations, and Trial Monitoring
• Type: Contributed
• Date/Time: Sunday, August 8, 2021 : 1:30 PM to 3:20 PM
• Sponsor: Biopharmaceutical Section
• Author(s): Xiaoyan Liu* and Zifei Han and Chanmin Kim and Gheorghe Doros
• Companies: Boston University and University of International Business and Economics and Sungkyunkwan University and Boston University
• Keywords: Placebo response; SPCD; Treatment effect; Principal stratification; EM algorithm

Abstract

In clinical trials, placebo response is a beneficial effect arising from the patient’s expectations for the treatment. The Sequential Parallel Comparison Design (SPCD), a two-stage design was proposed to address the shortcomings of the classical design. In SPCD, a weighted average of Stage 1 relative treatment difference among overall population and Stage 2 relative treatment difference among placebo nonresponder was used as the efficacy measure. However, this weighted average is not well-defined, and it lacks clinical interpretation. In this work, under the principal stratification framework, we assume the overall target population is a mixture of three latent strata: Always Responders, Never Responders, and Drug-only Responders. We propose treatment effects within each stratum enhanced by Stage 2 of SPCD under constancy assumption and estimate them via the Expectation maximization (EM) algorithm. The standard errors of estimated parameters are obtained by Louis method under the missing information principle. An extensive simulation study is conducted to evaluate the proposed methods. We also apply our method to an actual SPCD trial of antidepressant therapy.