A simulation‐based comparison of estimation methods for adaptive and classical group sequential clinical trials

2021 ◽  
Author(s):  
Bryan S. Nelson ◽  
Lingyun Liu ◽  
Cyrus Mehta
Keyword(s):  
Clinical Trials ◽  
Classical Group ◽  
Estimation Methods ◽  
Group Sequential ◽  
Simulation Based

scholarly journals Designing one-sided group sequential clinical trials to detect a mixture alternative

2018 ◽  
Vol 37 (2) ◽  
pp. 268-291
Author(s):  
Hua Peng ◽  
Daniel R. Jeske ◽  
Ashis SenGupta ◽  
Weixin Yao
Keyword(s):  
Clinical Trials ◽  
Group Sequential

A New Procedure for Group Sequential Analysis in Clinical Trials

Biometrics ◽  
1992 ◽  
Vol 48 (2) ◽  
pp. 373 ◽  
Author(s):  
Bruno Falissard ◽  
Joseph Lellouch
Keyword(s):  
Clinical Trials ◽  
Sequential Analysis ◽  
Group Sequential ◽  
Group Sequential Analysis

scholarly journals Statistical Monitoring of Clinical Trials Using Brownian Bridges

2016 ◽  
Vol 6 (1) ◽  
pp. 142
Author(s):  
Qiang Zhang ◽  
Michael R. Kosorok
Keyword(s):  
Clinical Trials ◽  
Type I Error ◽  
Brownian Bridge ◽  
Type I ◽  
Group Sequential Design ◽  
Group Sequential ◽  
Cancer Trial ◽  
Statistical Monitoring ◽  
Brownian Bridges ◽  
Group Sequential Methods

The Brownian bridge is not yet used widely in the statistical monitoring of clinical trials. In this paper, we investigate properties of the Brownian bridge and formally derive monitoring rules from these results. We will present four related main methods: (1). derivation of group sequential boundaries; (2). calculation of conditional power; (3). a new alpha spending function and (4). repeated confidence intervals, all under a Brownian bridge framework. Simulation results show that the type I error rate is well controlled and power is satisfactory for the group sequential design. We apply the proposed methods to monitor the interim results from the Beta Blocker Heart Attack Trial (BHAT) and a Head and Neck cancer trial with comparisons to the commonly used monitoring tools. Overall, the proposed methods when used together as one framework are more powerful and sensitive to interim positive and negative trends that are clinically meaningful and lead to timely early stopping with potentially more savings on sample sizes, time and costs. These tools are valuable additions to the existing group sequential methods which can be utilized in trial design, routine monitoring, and to answer important questions from data monitoring committees.

Analyses of group sequential clinical trials

1989 ◽  
Vol 10 (4) ◽  
pp. 222-230 ◽  
Author(s):  
Wolfgang Koepcke
Keyword(s):  
Clinical Trials ◽  
Group Sequential
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