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Unequal allocation and allocation concealment

Kuznetsova and Tymofyeyev [1] thoughtfully addressed the preservation of the allocation ratio when challenged by (restricted) unequal randomization, and we are in substantial agreement with the paper in terms of the approach taken, the methods used, and the conclusions drawn. Our areas of disagreement are somewhat limited but are still of great importance in the grand scheme of validity in randomized trials, and so we shall emphasize these few areas of disagreement. First, it was suggested that permuted blocks are safe in masked studies if the block sizes are small but should not be used otherwise. We certainly agree that seat belts should be worn when driving in inclement weather, but we are not so much in agreement with the part about dispensing with them when driving in fair weather. The seat belt is an insurance policy against accidents that cannot be predicted, and these may occur even in fair weather. Likewise, we must take exception with the sharp distinction drawn between masked and unmasked trials. As noted in Section 1.8 of [2], the more useful distinction is between the attempt, or process, or masking, and the result, or success, of the endeavor. It is clear that a study planned as masked can be known with certainty to have become unmasked, and this issue has arisen in some well publicized trials (for example, a 1975 trial of vitamin C [3]), but it is far more difficult to imagine that a study planned as masked could be known with certainty to have remained masked, even at the end of the trial. How can one convincingly demonstrate the absence of knowledge on the part of the patients and investigators? But even if we grant that a study could, at its conclusion, be declared to have remained perfectly masked up until the time when the data base was locked and the blind was broken, this would still not in any way mean that the success of the masking could have been anticipated ahead of time. At the time that the study is being planned and the permuted block procedure is being considered, there is no way to know how masked or unmasked the trial will turn out to be, given, for example, the possibility of differential side effects that will make obvious which patients received which treatments. So when, we ask, would it ever be OK to drive without a seat belt or to use permuted blocks? We are hard pressed to find any realistic situations for either [4, 5]. If we are not prepared to accept masking at face value, then we must also question the decision to emphasize unconditional probabilities. Any unmasking allows a researcher to replace the unconditional probabilities with the now more relevant conditional ones, which are conditioned on what has already been observed of the sequence of prior allocations. If the masking is perfect, then the prior allocations would not be known, and there would be no basis for replacing the original unconditional probabilities with the conditional probabilities, which would simply revert back to the unconditional probabilities. So, in summary, the conditional probabilities, or at least one set of conditional probabilities (it may not be clear which allocations to condition on if there is only partial unmasking), are relevant in all situations, and the unconditional ones are relevant only if masking is perfect, which we are loath to accept.