Interim analysis is important in a large clinical trial for ethical and cost considerations. Sometimes, an interim analysis needs to be performed at an earlier than planned time point. In that case, methods using stochastic curtailment are useful in examining the data for early stopping while controlling the inflation of type I and type II errors. We consider a three-arm randomized study of treatments to reduce perioperative blood loss following major surgery. Owing to slow accrual, an unplanned interim analysis was required by the study team to determine whether the study should be continued. We distinguish two different cases: when all treatments are under direct comparison and when one of the treatments is a control. We used simulations to study the operating characteristics of five different stochastic curtailment methods. We also considered the influence of timing of the interim analyses on the type I error and power of the test. We found that the type I error and power between the different methods can be quite different. The analysis for the perioperative blood loss trial was carried out at approximately a quarter of the planned sample size. We found that there is little evidence that the active treatments are better than a placebo and recommended closure of the trial.
Bonferroni adjustment, Conditional power, Interim analysis, Predictive power, Stochastic curtailment, Stopping time
Journal of the Royal Statistical Society - Series C: Applied Statistics
Royal Statistical Society
LEUNG, Denis H. Y.; WANG, You-Gan; and AMAR, David.
Early stopping by using stochastic curtailment in a three-arm sequential trial. (2003). Journal of the Royal Statistical Society - Series C: Applied Statistics. 52, (2), 139-152. Research Collection School Of Economics.
Available at: https://ink.library.smu.edu.sg/soe_research/106
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