A Model-Based Meta-Analysis Framework Quantifying Drivers of Placebo Response in Atopic Dermatitis Trials

Atopic dermatitis (AD) clinical trials exhibit substantial placebo response variability, confounding efficacy assessments of novel therapies. Traditional meta-analyses have identified potential contributors to this variability but rely on single time-point estimates, which fail to account for dynamic, longitudinal response patterns across trials. To overcome this limitation, we developed a model-based meta-analysis (MBMA) framework that characterizes time-course projections of EASI-75 placebo responses while accounting for key covariates. A systematic literature review identified 40 moderate-to-severe AD trials (18 Phase 2, 22 Phase 3), encompassing 4827 patients, suitable for longitudinal modeling. Modeling results highlighted concomitant therapy as a significant driver of placebo response, with trials permitting topical corticosteroids (TCS) demonstrating a 1.8-fold increase in EASI-75 placebo rates compared to trials without concomitant therapy. Additionally, baseline disease severity of the study population, as reflected by the mean baseline EASI score, was inversely associated with placebo response; each 1-point increase in baseline EASI reduced EASI-75 placebo rates at Weeks 12 and 16 by 0.96-fold. Time-course modeling suggested that placebo responses plateaued by Week 12, with EASI-75 outcomes at Week 12 capturing 94% of the projected response at Week 16. Overall, this MBMA framework provides quantitative guidance to optimize clinical trial design, refine power calculations, and improve the differentiation between therapeutic and placebo effects in AD drug development.