Is restricted randomisation necessary?

Abstract

Problems with restricted randomisation Introducing any form of restricted randomisation increases the risk of subversion (conscious or unconscious) and technical error. Most examples of known subversion relate to situations where allocation sequences are public knowledge or the concealment of the allocation is inadequate, such as using sealed envelopes that can be tampered with.3 4 However, this type of subversion is not specific to restricted randomisation. What will come next? Credit: PHOTOS.COM With restricted randomisation subversion remains possible even when adequate precautions have been taken to conceal the randomisation sequence.5 In an open trial, if we know the block size and we keep a record of previous allocations then we will always be certain about the last allocation in the block. Furthermore, we will also often be able to guess the penultimate allocation correctly. If trialists make predictions only when they are certain of the next treatment, then for a block size of four they will be able to predict 33% of the treatments and for a block size of six they will be able to predict 25%. However, if the trialist simply guesses that the next treatment will be opposite to the previous treatment, then for a block size of four they will be correct 71% of the time and for a block size of six they will be correct 68% of the time.6 Predictability can be reduced by using larger block sizes or more than one block size. However, the best way to reduce predictability is to keep the block size hidden and to blind all people in the trial to the treatment the participants are allocated. When minimisation is used, researchers have advocated adding a random element to the minimisation algorithm to reduce predictability.7 The dangers of using restricted allocation were shown in a recent survey of 25 clinicians and research nurses in which four (16%) admitted to keeping a log of previous allocations to help predict future ones.8 Restricted allocation increases the complexity of the randomisation process and errors could be introduced into the randomisation. For example, the comparative obstetric mobile epidural trial used minimisation to allocate participants to treatments to improve balance on age and ethnicity.9 Unfortunately, the software had an error, which resulted in large imbalances in both of these variables. The trial had to be started again at considerable cost. One of us (DJT) was an external member of the steering group of another MRC funded trial in which a minimisation algorithm with an error was introduced part way through. Fortunately, this error was identified before many participants had been allocated to the treatments. These two examples suggest that even with well funded and conducted trials human error can potentially lead to disaster.