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A Model-Based Meta-Analysis Framework Quantifying Drivers of Placebo Response in Atopic Dermatitis Trials
Jean C Serrano1, John Maringwa2, Roel Straetemans3
1Johnson & Johnson, Cambridge, Massachusetts, USA.
CPT: Pharmacometrics & Systems Pharmacology
|November 17, 2025
Summary
This study introduces a model-based meta-analysis (MBMA) for atopic dermatitis (AD) clinical trials. It reveals that concomitant therapies and baseline disease severity significantly impact placebo responses, offering insights for better trial design.
Area of Science:
- Dermatology
- Clinical Trials
- Biostatistics
Background:
- Atopic dermatitis (AD) clinical trials face challenges due to high placebo response variability, complicating the evaluation of new treatments.
- Existing meta-analyses use single time-point data, failing to capture longitudinal placebo response dynamics.
Purpose of the Study:
- To develop and apply a model-based meta-analysis (MBMA) framework to analyze time-course projections of EASI-75 placebo responses in AD trials.
- To identify key covariates influencing placebo response variability in moderate-to-severe AD clinical trials.
Main Methods:
- A systematic literature review identified 40 Phase 2/3 AD trials with 4827 patients suitable for longitudinal modeling.
- A model-based meta-analysis (MBMA) was employed to project EASI-75 placebo response over time, incorporating covariates.
Main Results:
- Concomitant therapy, specifically topical corticosteroids (TCS), increased EASI-75 placebo rates 1.8-fold.
- Higher baseline EASI scores were associated with lower placebo response rates (0.96-fold reduction per 1-point increase).
- Placebo responses plateaued by Week 12, with Week 12 outcomes reflecting 94% of Week 16 projected responses.
Conclusions:
- The MBMA framework provides a robust method for analyzing longitudinal placebo responses in AD trials.
- Findings offer quantitative guidance for optimizing clinical trial design, power calculations, and distinguishing therapeutic effects from placebo responses in AD drug development.
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