In an adaptive seamless phase II/III clinical trial interim
analysis data are used for treatment selection, enabling resources to be focussed on comparison of more effective treatment(s) with a control. In this paper we compare two methods recently proposed to enable use of short-term endpoint data for decision-making at the interim analysis. The comparison focusses on the power and the probability of correctly identifying the most promising treatment. We show that the choice of method depends on how well short-term data predict the best treatment, which may be measured by the correlation between treatment effects on short-term and long-term endpoints