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Actuarial Approach01:20

Actuarial Approach

The actuarial approach, a statistical method originally developed for life insurance risk assessment, is widely used to calculate survival rates in clinical and population studies. This method accounts for participants lost to follow-up or those who die from causes unrelated to the study, ensuring a more accurate representation of survival probabilities.
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Life Tables

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Establishing a Competing Risk Regression Nomogram Model for Survival Data
04:57

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Published on: October 23, 2020

Sample size formulae for two-stage randomized trials with survival outcomes.

Zhiguo Li1, Susan A Murphy

  • 1Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, North Carolina 27710, U.S.A.

Biometrika
|February 25, 2012
PubMed
Summary

Calculating sample sizes for two-stage randomized trials is complex. This study offers simple, conservative formulas using upper variance bounds, simplifying planning for adaptive treatment strategies.

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Area of Science:

  • Clinical Trials
  • Biostatistics
  • Medical Research Methodology

Background:

  • Two-stage randomized trials are increasingly vital for adaptive treatment strategies.
  • These trials involve sequential treatment assignments based on patient response.
  • Calculating sample sizes for these complex designs with failure time outcomes is challenging.

Purpose of the Study:

  • To develop simplified and conservative sample size formulas for two-stage randomized trials.
  • To address the complexities in variance estimation for failure time outcomes in adaptive trials.
  • To provide practical tools for researchers planning such studies.

Main Methods:

  • Utilized upper bounds on variances to derive simplified sample size formulas.
  • Employed a weighted Kaplan-Meier estimator for survival probabilities.
  • Incorporated a weighted log-rank test for statistical analysis.
  • Ensured formulas require only standard single-stage trial assumptions.

Main Results:

  • Developed simple, albeit conservative, sample size formulas for two-stage trials.
  • The proposed formulas are only mildly conservative in common settings.
  • The method simplifies sample size calculations by avoiding complex variance dependencies.
  • The formulas are based on established statistical methods like weighted Kaplan-Meier and log-rank tests.

Conclusions:

  • The proposed sample size formulas offer a practical solution for planning two-stage randomized trials.
  • These formulas reduce the complexity of sample size calculations for adaptive treatment strategies.
  • The approach provides a reliable and only mildly conservative estimation for trial planning.