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Sample size determination for time-to-event endpoints in randomized selection trials with generalized exponential

Muhammad Hamza Akbar1, Sajid Ali1, Ismail Shah2,1

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|March 8, 2024
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Summary

This study addresses sample size calculation for randomized trials with time-to-event endpoints, focusing on progression-free survival. It develops methods for exponential, Weibull, and generalized exponential distributions, crucial for accurate clinical trial design.

Keywords:
Generalized exponential distributionRandomized control trialsSample size determinationWeibull distribution

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Area of Science:

  • Clinical Trials
  • Biostatistics
  • Survival Analysis

Background:

  • Randomized selection trials often lack control groups.
  • Existing sample size methodologies for time-to-event endpoints are limited, particularly beyond the exponential distribution.
  • Progression-free survival is increasingly used as a primary endpoint but poses challenges for sample size determination.

Purpose of the Study:

  • To develop and present methodologies for sample size calculation in randomized trials with time-to-event endpoints.
  • To extend sample size calculations beyond the exponential distribution to include Weibull and generalized exponential distributions.
  • To address the complexities introduced by progression-free survival as a primary endpoint.

Main Methods:

  • The study assumes time-to-event endpoints follow exponential, Weibull, or generalized exponential distributions.
  • It focuses on developing sample size calculation methodologies for these distributions.
  • The research addresses the specific challenges of using progression-free survival as a primary endpoint.

Main Results:

  • Methodologies for sample size determination are presented for exponential, Weibull, and generalized exponential distributions.
  • The study provides a framework for calculating sample sizes in randomized trials with these time-to-event endpoints.
  • The findings are relevant to trials emphasizing progression-free survival.

Conclusions:

  • Accurate sample size calculation is critical for the validity of randomized trials.
  • The developed methodologies enhance the ability to compare treatment groups, especially with progression-free survival endpoints.
  • This work provides essential statistical tools for modern clinical trial design and analysis.