A re-randomisation design for clinical trials

Abstract

BackgroundRecruitment to clinical trials is often problematic, with many trials failing to recruit to their target sample size. As a result, patient care may be based on suboptimal evidence from underpowered trials or non-randomised studies.MethodsFor many conditions patients will require treatment on several occasions, for example, to treat symptoms of an underlying chronic condition (such as migraines, where treatment is required each time a new episode occurs), or until they achieve treatment success (such as fertility, where patients undergo treatment on multiple occasions until they become pregnant). We describe a re-randomisation design for these scenarios, which allows each patient to be independently randomised on multiple occasions. We discuss the circumstances in which this design can be used.ResultsThe re-randomisation design will give asymptotically unbiased estimates of treatment effect and correct type I error rates under the following conditions: (a) patients are only re-randomised after the follow-up period from their previous randomisation is complete; (b) randomisations for the same patient are performed independently; and (c) the treatment effect is constant across all randomisations. Provided the analysis accounts for correlation between observations from the same patient, this design will typically have higher power than a parallel group trial with an equivalent number of observations.ConclusionsIf used appropriately, the re-randomisation design can increase the recruitment rate for clinical trials while still providing an unbiased estimate of treatment effect and correct type I error rates. In many situations, it can increase the power compared to a parallel group design with an equivalent number of observations.Electronic supplementary materialThe online version of this article (doi:10.1186/s12874-015-0082-2) contains supplementary material, which is available to authorized users.

How do you design randomised trials for smaller populations? A framework

“…However, re-randomising patients who have completed their predefined follow-up from a previous randomisation in the trial and who continue to meet the trial’s eligibility criteria an arbitrary number of times can still result in valid statistical inference about treatment effectiveness [18]. Unlike crossover trials, patients do not have a predefined number of treatment periods and the treatment assignments in the sequence do not depend on previous or subsequent assignments.…”

“…If the majority of patients are randomised on multiple occasions then the analysis can be based on within-patient comparisons, potentially gaining much efficiency [18]. …”

Using re-randomization to increase the recruitment rate in clinical trials – an assessment of three clinical areas

“…The re-randomization design has been proposed as a way of increasing the recruitment rate compared to parallel-group trials [9]. The re-randomization design involves re-enrolling and re-randomizing patients who require further treatment after their initial enrollment is complete.…”

“…The re-randomization design involves re-enrolling and re-randomizing patients who require further treatment after their initial enrollment is complete. An overview of this design is provided in Table 1, and further details are available in a previous publication [9]. The re-randomization design can be used in situations where (1) patients may require treatment on multiple occasions, (2) the intervention(s) under study would be used for each new treatment episode, and (3) the intervention duration and length of the follow-up period for each randomization are less than the overall length of the trial recruitment period.…”

“…Re-randomization trials can provide unbiased estimates of treatment effect and correct type I error rates provided: (1) patients are only re-enrolled and re-randomized after the follow-up period from their previous treatment episode is complete, and (2) randomizations for the same patient are performed independently [9]. It is important to note that the number of times that each patient is enrolled is not specified in advance, and instead depends on the number of treatment episodes that they experience during the course of the trial.…”