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Simulation study for evaluating the performance of response-adaptive randomization.

Yining Du1, Xuan Wang2, J Jack Lee3

  • 1Department of Biostatistics, The University of Texas MD Anderson Cancer Center, 1400 Pressler Street, Houston, TX 77030, USA; Division of Biostatistics, School of Public Health, The University of Texas Health Science Center at Houston, 1200 Pressler Street, Houston, TX 77030, USA.

Contemporary Clinical Trials
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PubMed
Summary
This summary is machine-generated.

Response-adaptive randomization (RAR) trials can assign more patients to effective treatments. Sequential posterior mean (SPM) is recommended among RAR designs for better outcomes and efficiency in clinical trials.

Keywords:
Allocation probabilityBayesian adaptive designEfficacy early stoppingOperating characteristicsPatient horizon

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Area of Science:

  • Clinical Trial Design
  • Biostatistics
  • Medical Research Methodology

Background:

  • Response-adaptive randomization (RAR) adjusts treatment assignment probabilities based on interim results.
  • RAR aims to ethically allocate more patients to superior treatments during a trial.
  • Equal randomization (ER) assigns patients uniformly, serving as a standard comparison.

Purpose of the Study:

  • To compare the performance of equal randomization (ER) with three response-adaptive randomization (RAR) designs.
  • To evaluate RAR designs based on patient allocation to the superior arm, overall response rate, statistical power, and trial size.
  • To assess the impact of early stopping rules on the comparison between RAR and ER designs.

Main Methods:

  • Comparison of ER with Bayesian adaptive randomization (BAR), sequential maximum likelihood (SML), and sequential posterior mean (SPM) designs.
  • Fixed patient horizon with varied trial enrollment numbers.
  • Analysis included proportion of patients in the superior arm, overall response rate, statistical power, and total patients enrolled, with and without early stopping rules.

Main Results:

  • Without early stopping, ER is favored when future patient pools are large; RAR is better for large treatment differences or small future patient pools.
  • Early stopping rules reduced performance differences between RAR and ER designs.
  • SPM demonstrated a higher proportion of patients in the better arm and a higher overall response rate compared to BAR, with similar power and trial size to ER.

Conclusions:

  • Both RAR and ER designs can achieve desirable statistical properties with careful parameter selection.
  • The sequential posterior mean (SPM) design is recommended among the evaluated RAR methods.
  • The choice between RAR and ER depends on ethical considerations, investigator preference, and trial logistics.