Open Access: Conditional power and friends: The why and how of (un)planned, unblinded sample size recalculations in confirmatory trials

Each week, we select a recently published Open Access article to feature. This week’s article comes from Statistics in Medicine and examines approaches to estimating conditional power.

The article’s abstract is given below, with the full article available to read here.

Kunzmann, KGrayling, MJLee, KMRobertson, DSRufibach, KWason, JMSConditional power and friends: The why and how of (un)planned, unblinded sample size recalculations in confirmatory trialsStatistics in Medicine20221– 14. doi:10.1002/sim.9288

Adapting the final sample size of a trial to the evidence accruing during the trial is a natural way to address planning uncertainty. Since the sample size is usually determined by an argument based on the power of the trial, an interim analysis raises the question of how the final sample size should be determined conditional on the accrued information. To this end, we first review and compare common approaches to estimating conditional power, which is often used in heuristic sample size recalculation rules. We then discuss the connection of heuristic sample size recalculation and optimal two-stage designs, demonstrating that the latter is the superior approach in a fully preplanned setting. Hence, unplanned design adaptations should only be conducted as reaction to trial-external new evidence, operational needs to violate the originally chosen design, or post hoc changes in the optimality criterion but not as a reaction to trial-internal data. We are able to show that commonly discussed sample size recalculation rules lead to paradoxical adaptations where an initially planned optimal design is not invariant under the adaptation rule even if the planning assumptions do not change. Finally, we propose two alternative ways of reacting to newly emerging trial-external evidence in ways that are consistent with the originally planned design to avoid such inconsistencies.
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