Sequential trials in the context of competing risks: Concepts and case study, with R and SAS code

Area of Science:

• Statistics
• Biostatistics
• Clinical Trials

Background:

• Sequential designs allow for early stopping of clinical trials based on accumulating data.
• Competing risks methodology is essential when multiple event types can occur, influencing overall survival analysis.
• While theoretically explored, the practical integration of sequential designs with competing risks remains underexplored.

Purpose of the Study:

• To provide applied statisticians with a foundational understanding of sequential design theory.
• To explain competing risks methodology for practical implementation.
• To demonstrate the combined application of these methodologies in real-world scenarios.

Main Methods:

• Review of established sequential design principles.
• Explanation of competing risks analysis techniques.
• Illustration through a comprehensive case study.
• Provision of R and SAS code for practical application.

Main Results:

• Demonstration of how to practically combine sequential designs with competing risks analysis.
• Case study highlights the utility and challenges of the integrated approach.
• Availability of reproducible code for applied statisticians.

Conclusions:

• The integration of sequential designs and competing risks methodology is feasible and beneficial for applied statisticians.
• Practical guidance and code are crucial for the adoption of these combined methods.
• This work facilitates more efficient and informative clinical trial designs under competing risks.