Designing Efficient Multicenter Trials With a Maximin Strategy

Area of Science:

• Biostatistics
• Clinical Trial Design
• Health Economics

Background:

• Multicenter trials are crucial for generalizability but require careful design to manage resources.
• Optimizing participant allocation and center/participant balance is key for efficient trials.
• Existing optimal designs struggle with unknown variance parameters, impacting power guarantees.

Purpose of the Study:

• To develop and present efficient multicenter trial designs that minimize sample size and budget.
• To introduce maximin designs that guarantee statistical power across a range of unknown parameters.
• To extend existing designs by considering fixed numbers of centers or participants per center.

Main Methods:

• Derivation of maximin designs for two-treatment multicenter trials with continuous outcomes.
• Optimization of treatment allocation ratios and the balance between number of centers and participants per center.
• Development of sample size calculation methods for fixed or optimized center/participant numbers.

Main Results:

• Maximin designs provide guaranteed power levels under uncertainty of variance parameters.
• Designs allow optimization of both participant allocation and the number of centers versus participants per center.
• The study demonstrates potential budget savings and simplifies calculations with an R Shiny app.

Conclusions:

• Maximin designs offer a robust approach to sample size and budget optimization in multicenter trials.
• The developed methods and tools facilitate practical implementation of efficient trial designs.
• These designs are valuable for ensuring adequate statistical power while minimizing resource expenditure in clinical research.