Background: Recruitment to clinical trials is often problematic, with many trials failing to recruit to their target\nsample size. As a result, patient care may be based on suboptimal evidence from underpowered trials or\nnon-randomised studies.\nMethods: For many conditions patients will require treatment on several occasions, for example, to treat symptoms\nof an underlying chronic condition (such as migraines, where treatment is required each time a new episode\noccurs), or until they achieve treatment success (such as fertility, where patients undergo treatment on multiple\noccasions until they become pregnant). We describe a re-randomisation design for these scenarios, which allows\neach patient to be independently randomised on multiple occasions. We discuss the circumstances in which this\ndesign can be used.\nResults: The re-randomisation design will give asymptotically unbiased estimates of treatment effect and correct type I\nerror rates under the following conditions: (a) patients are only re-randomised after the follow-up period from their\nprevious randomisation is complete; (b) randomisations for the same patient are performed independently; and (c) the\ntreatment effect is constant across all randomisations. Provided the analysis accounts for correlation between\nobservations from the same patient, this design will typically have higher power than a parallel group trial with\nan equivalent number of observations.\nConclusions: If used appropriately, the re-randomisation design can increase the recruitment rate for clinical\ntrials while still providing an unbiased estimate of treatment effect and correct type I error rates. In many\nsituations, it can increase the power compared to a parallel group design with an equivalent number of\nobservations.
Loading....