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A simulation study of outcome adaptive randomization in multi-arm clinical trials
J Kyle Wathen1, Peter F Thall2
11 Model Based Drug Development, Statistical Decision Sciences, Janssen Research & Development, LLC, Titusville, NJ, USA.
Clinical Trials (London, England)
|October 7, 2017
Summary
Outcome adaptive randomization in multi-arm clinical trials often yields lower probabilities of selecting superior treatments compared to equal randomization. A modified adaptive method shows promise but still has limitations.
Area of Science:
- Clinical Trial Design
- Biostatistics
- Medical Research Methodology
Background:
- Equal randomization is the standard for unbiased clinical trial comparisons.
- Outcome adaptive randomization methods aim to improve trial efficiency and ethics by adjusting probabilities based on interim data.
- The performance of adaptive randomization in multi-arm trials remains under-investigated.
Purpose of the Study:
- To systematically evaluate and compare Bayesian adaptive randomization methods against equal randomization in multi-arm clinical trials via simulation.
- To assess the impact of trial design features, such as control arms and early stopping rules, on selection probabilities.
- To identify adaptive randomization strategies with desirable properties for multi-arm settings.
Main Methods:
- A simulation study was conducted using five-arm clinical trials.
- Four Bayesian adaptive randomization methods, incorporating an initial equal randomization burn-in and modifications to prevent extreme probabilities, were evaluated.
- Trials with and without a control arm, including options for early futility stopping and final treatment selection, were analyzed across various scenarios and sample sizes.
Main Results:
- Several commonly used adaptive randomization methods demonstrated very low probabilities of correctly selecting a superior treatment in trials with a control arm (N=250 or 500).
- An adaptive method with an initial equal randomization burn-in and probabilities restricted to 0.10-0.90 showed favorable sample size imbalance but a reduced probability of selecting a superior treatment compared to equal randomization.
- In multi-arm trials, most adaptive methods resulted in significantly lower probabilities of selecting superior treatments than equal randomization.
Conclusions:
- Many current adaptive randomization methods offer limited benefit in multi-arm clinical trials, often reducing the likelihood of identifying superior treatments.
- Adaptive randomization without a control arm can further decrease the probability of selecting superior treatments, especially when treatment effect differences are small.
- Careful selection and modification of adaptive randomization strategies are crucial for effective multi-arm clinical trial design.
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