• Michael A Proschan.
• National Institute of Allergy and Infectious Diseases, Bethesda, MD, USA.
• Clin Trials. 2017 Oct 1; 14 (5): 425-431.

AbstractDespite the best efforts of investigators, problems forcing design changes can occur in clinical trials. Changes are usually relatively minor, but sometimes not. The primary endpoint or analysis may need to be revised, for example. It is common to regard any conclusion from such a tarnished trial as hypothesis-generating rather than definitive. This article reviews a very useful technique, re-randomization tests, for dealing with such anomalies. Re-randomization tests remain valid for testing a strong null hypothesis that treatment has no effect on the data that led to design changes. Another way of expressing this is that the data used to inform a design change must give no information about the treatment labels. This restriction has implications for limiting the amount of information examined by a committee deciding whether to make design alterations. While nothing can eliminate the pall cast by breaches of protocol, re-randomization tests following blinded and limited data examination go a long way toward amelioration.

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