Publication Type

Journal Article

Version

publishedVersion

Publication Date

5-2003

Abstract

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.

Keywords

Bonferroni adjustment, Conditional power, Interim analysis, Predictive power, Stochastic curtailment, Stopping time

Discipline

Econometrics

Research Areas

Econometrics

Publication

Journal of the Royal Statistical Society - Series C: Applied Statistics

Volume

52

Issue

2

First Page

139

Last Page

152

ISSN

0035-9254

Identifier

10.1111/1467-9876.00394

Publisher

Royal Statistical Society

Additional URL

https://doi.org/10.1111/1467-9876.00394

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