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A simulation-based comparison of estimation methods for adaptive and classical group sequential clinical trials.

Bryan S Nelson1, Lingyun Liu2, Cyrus Mehta1,3

  • 1Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.

Pharmaceutical Statistics
|December 27, 2021
PubMed
Summary

For adaptive clinical trials, the backward image confidence interval (BWCI) offers accurate parameter estimation, unlike the conservative repeated confidence interval (RCI) or unreliable naive confidence interval (CI). Use BWCI for final estimates and RCI for interim looks.

Keywords:
adaptive clinical trialbackward-image confidence intervalrepeated confidence intervalsample-size reestimationstagewise adjusted confidence interval

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Area of Science:

  • Biostatistics
  • Clinical Trial Design
  • Statistical Inference

Background:

  • Statistical methods for hypothesis testing in adaptive group sequential clinical trials are established.
  • Methods for statistically valid point estimates and confidence intervals in adaptive designs require further understanding.

Purpose of the Study:

  • To evaluate the coverage and bias of confidence intervals for parameter estimation in adaptive clinical trials.
  • To compare the performance of the backward image confidence interval (BWCI), repeated confidence interval (RCI), and naive confidence interval (CI).

Main Methods:

  • Conducted a simulation study to explore parameter estimation after sample size reestimation.
  • Investigated methods with strong control of type-I error in adaptive group sequential designs.
  • Assessed coverage properties and potential biases of different confidence interval methods.

Main Results:

  • The backward image confidence interval (BWCI) generally provided exact coverage.
  • The naive confidence interval (CI) demonstrated inconsistent coverage.
  • The repeated confidence interval (RCI) offered conservative coverage with noted asymmetry, though within acceptable bounds.

Conclusions:

  • Strongly recommend the use of BWCI and median unbiased estimate (MUE) for final parameter estimation in adaptive trials.
  • Advise using RCI during interim looks and avoiding naive CIs.
  • Findings are applicable to both adaptive and classical group sequential designs.