• The rationale for using a Bayesian approach to interim analyses is explained.
• The formulation of interim decision rules on the basis of posterior and predictive probability is introduced and evaluated using a case study.
• The value of simulations are included to assess the merits of the different decision rules and the relative timing of interim analyses is illustrated.

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