Time trends with response-adaptive randomization: The inevitability of inefficiency

Response-adaptive randomization, which changes the randomization ratio as a randomized clinical trial progresses, is inefficient as compared to a fixed 1:1 randomization ratio in terms of increased required sample size. It is also known that response-adaptive randomization leads to biased treatment effects if there are time trends in the accruing outcome data, for example, due to changes in the patient population being accrued, evaluation methods, or concomitant treatments. Response-adaptive-randomization analysis methods that account for potential time trends, such as time-block stratification or re-randomization, can eliminate this bias. However, as shown in this Commentary, these analysis methods cause a large additional inefficiency of response-adaptive randomization, regardless of whether a time trend actually exists.

Automated summary

Response-adaptive randomization is less efficient in terms of increased required sample size compared to fixed 1:1 randomization ratio, and it leads to biased treatment effects when there are time trends. Analysis methods that account for potential time trends can eliminate this bias but contribute to additional inefficiency of response-adaptive randomization.