A General Approach for Estimating Stopping Probabilities of Large Group Sequential Trials in Life-Threatening Conditions Monitoring Binary Efficacy and Safety Outcomes

• Activity Number: 522
• Type: Contributed
• Date/Time: Wednesday, August 1, 2012 : 10:30 AM to 12:20 PM
• Sponsor: Biopharmaceutical Section
• Author(s): Yanqiu Weng*+ and Wenle Zhao and Yuko Palesch
• Companies: Medical University of South Carolina and Medical University of South Carolina and Medical University of South Carolina
• Keywords: Data and Safety Monitoring Committee ; efficacy ; group sequential design ; power ; safety ; type I error

Abstract

In large confirmatory trials for life-threatening conditions, some adverse events are not rare or unexpected, and can be formally monitored under a statistical guideline. However, it is unknown how much safety monitoring would impact the error probabilities for efficacy analyses. On the other side, the decision making from Data Safety Monitoring Committees (DSMC) on early stopping a study is flexible, but most methods and available software for alpha spending and sample size calculation are based on the assumption that DSMCs strictly complies with statistical guidelines, which is not realistic. We develop a new approach to estimate the stopping probabilities for a bivariate efficacy-safety response in large group sequential trials. In addition to handling the multiplicity issue for multiple outcomes, the new approach is able to provide power estimations under various assumptions on data monitoring practices. The method is verified by Monte Carlo simulation and is demonstrated based on a real stroke trial. The findings from this study suggest that formal safety monitoring in life-threatening conditions could have a dramatic impact on error probabilities for efficacy analyses.