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Confounding due to changing background risk in adaptively randomized trials.
Ari M Lipsky1, Sander Greenland
1Gertner Institute for Epidemiology and Health Policy Research, Chaim Sheba Medical Center, Tel Hashomer 52621, Israel. aril@alum.mit.edu
Clinical Trials (London, England)
|May 26, 2011
Summary
Adaptive randomization in clinical trials can introduce bias due to time trends in disease incidence. Adjustments are necessary to ensure accurate effect estimates when analyzing trial data.
Area of Science:
- Biostatistics
- Clinical Trial Design
Background:
- Adaptive trials offer efficiency gains but are susceptible to unique biases.
- Time trends in disease incidence can complicate adaptive randomization.
Purpose of the Study:
- To identify and illustrate a specific bias in adaptive randomization.
- Focus on bias arising from concurrent changes in subject allocation and background risk.
Main Methods:
- Utilized a potential-outcome model.
- Employed directed acyclic graphs (DAGs) for bias illustration.
- Examined interplay between exchangeability and changing randomization proportions.
Main Results:
- Time trends in disease risk can bias crude effect estimates in adaptive trials.
- Naive data combination across trial stages can be misleading.
- Bias stems from non-exchangeability and shifting allocation ratios.
Conclusions:
- Adaptive randomization analysis requires addressing time trends in background risk.
- Methods for adjustment include stratification, trend modeling, and regression techniques.
- Risk-ratio and risk-difference analyses are considered.
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