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Randomization is crucial for fair treatment comparisons in early-phase oncology trials, even with small patient numbers. This method minimizes bias and confounding, ensuring reliable results for experimental therapies.

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Area of Science:

  • Clinical Trials Methodology
  • Biostatistics
  • Oncology Research

Background:

  • Randomization is a standard for fair treatment comparisons in clinical trials.
  • Investigators often forgo randomization in small, early-phase oncology trials due to convention or perceived low value.
  • This practice can lead to bias and confounding when comparing treatments.

Purpose of the Study:

  • To advocate for the use of randomization in small, early-phase oncology trials.
  • To demonstrate how randomization ensures fair treatment comparisons despite small sample sizes.
  • To provide practical guidelines and statistical tools for conducting small randomized trials.

Main Methods:

  • Discusses the potential for confounding and bias in non-randomized trials.
  • Presents Bayesian criteria for comparing treatments based on response and toxicity.
  • Offers guidelines for sample size determination, safety/futility monitoring, and randomization schemes.

Main Results:

  • Randomization eliminates confounding from prognostic variables, ensuring unbiased comparisons.
  • Bayesian methods facilitate the planning and analysis of small randomized trials.
  • Illustrates methods with a trial of engineered cells for graft-versus-host disease.

Conclusions:

  • Randomization is highly desirable and feasible in early-phase oncology trials.
  • It provides unbiased treatment comparisons essential for evaluating novel therapies.
  • The proposed Bayesian framework supports the implementation of small randomized trials.