A convenient formula for sample size calculations in clinical trials with multiple co-primary continuous endpoints

Area of Science:

• Biostatistics
• Clinical Trial Design
• Pharmaceutical Development

Background:

• Clinical trials increasingly use multiple co-primary endpoints to evaluate treatment efficacy.
• Determining appropriate sample sizes for trials with multiple correlated endpoints is complex.
• Existing methods often require advanced mathematical and programming expertise, limiting practical application.

Purpose of the Study:

• To develop a more accessible method for sample size calculation in clinical trials with multiple co-primary endpoints.
• To provide a practical formula and numerical tables for researchers in pharmaceutical drug development.
• To facilitate the design of clinical trials evaluating new treatments on continuous co-primary endpoints.

Main Methods:

• Development of a simplified formula for sample size calculation.
• Creation of accompanying numerical tables based on correlation patterns and effect size ratios.
• Inclusion of illustrative examples to demonstrate formula application.

Main Results:

• A user-friendly formula and tables are provided for sample size determination.
• The method simplifies calculations for clinical trials with two treatments and continuous co-primary endpoints.
• Convenient evaluation of required sample size is enabled by the provided tools.

Conclusions:

• The developed formula and tables enhance the practicality of sample size calculations for trials with multiple co-primary endpoints.
• This approach supports more widespread and efficient trial design in pharmaceutical research.
• Researchers can more readily determine adequate sample sizes, improving the rigor of clinical efficacy evaluations.