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  • 1Biometrics Division, H. Lundbeck A/S, Copenhagen, Denmark.

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|May 18, 2019
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Summary
This summary is machine-generated.

This paper bridges sequential designs and competing risks methodology for practical application. It offers statisticians guidance on combining these established methods with real-world case studies and code examples.

Keywords:
cause-specific hazardscompeting riskscumulative incidenceerror spending functionssequential trials

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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.