A simple method for the estimation of interaction bias in crossover studies.

The crossover trial is considered the most powerful means of determining the efficacy of new drugs. However this study design is frequently invalidated by treatment-by-period interaction. If, for example, the effect of the first treatment period carries on into the next one, then it influences the response to the latter period (carryover effect). A second problem is that there are no reliable statistical methods to test for this potential bias. This article takes issue with these problems and gives an alternative method for the detection of interaction simply by looking at the data. In a crossover without interaction the second period should be a true reflection of the first. If, however, the data of a treatment are better in the second period than in the first, a carryover effect is probable. If worse, a rebound phenomenon or a negative carryover effect is likely. If both treatments are better or worse, a time effect or some other external influence might be present. The authors illustrate this simple method by a summary of a few selected trials that have been published recently. This method enables not only the detection of interaction but also the differentiation between different types of interactions. Therefore, investigators are advised to use it in order to make sure that there are no unexpected problems.