Estimation of the relative difference (or relative risk reduction) under the sequential parallel comparison design

Area of Science:

• Clinical Trials Methodology
• Psychiatric Research
• Biostatistics

Background:

• High placebo response rates in psychiatric trials necessitate efficient study designs.
• Statistical significance does not always equate to clinical importance of treatment effects.
• Dichotomous patient responses pose challenges for traditional additive effect measures.

Purpose of the Study:

• To propose and evaluate methods for quantifying treatment effects in psychiatric trials using the sequential parallel comparison design.
• To address the limitations of risk differences for dichotomous outcomes in the presence of high placebo response rates.
• To introduce relative difference and relative risk reduction as meaningful measures of treatment effect.

Main Methods:

• Development of point and interval estimators for relative difference using weighted-least-squares and Mantel-Haenszel methods.
• Monte Carlo simulations to assess the finite-sample performance of the proposed estimators.
• Inclusion of a homogeneity test for relative differences across trial phases.

Main Results:

• The proposed estimators provide reliable measures of treatment effect for dichotomous outcomes in sequential parallel comparison designs.
• Monte Carlo simulations demonstrate the performance of the estimators across various scenarios.
• The study illustrates the application of these methods using a real-world clinical trial example.

Conclusions:

• Relative difference and relative risk reduction are valuable metrics for assessing treatment efficacy in psychiatric disorders with high placebo response.
• The sequential parallel comparison design, coupled with these effect measures, can enhance trial power and efficiency.
• The developed statistical methods offer a robust approach for analyzing clinical trial data in mental health research.