Results 211 to 220 of about 353,062 (253)

Software for complex group sequential designs

Contemporary Clinical Trials
Group sequential design (GSD) is a statistical methodology employed in clinical trials to enable interim analyses (IA) and potential early termination based on accumulating data. It has gained significant popularity in the field of clinical trials due to its ability to enhance decision-making and expedite the development of effective treatments.
Yujie, Zhao, Keaven, Anderson
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A practical guide to Bayesian group sequential designs

Pharmaceutical Statistics, 2013
AbstractBayesian approaches to the monitoring of group sequential designs have two main advantages compared with classical group sequential designs: first, they facilitate implementation of interim success and futility criteria that are tailored to the subsequent decision making, and second, they allow inclusion of prior information on the treatment ...
Gsponer T, Gerber F, Bornkamp B, Ohlssen D, Vandemeulebroecke M, Schmidli H   +5 more
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Group-Sequential and Adaptive Designs

2017
As motivated in Part I of this book, a major difficulty when planning a clinical trial with a composite primary endpoint or, as an alternative, with a single component as primary efficacy measure is to make valid planning assumptions on the required parameters and the expected effect size.
Geraldine Rauch, Svenja Schüler, Meinhard Kieser   +2 more
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Exact inference for adaptive group sequential designs

Statistics in Medicine, 2013
Methods for controlling the type‐1 error of an adaptive group sequential trial were developed in seminal papers by Cui, Hung, and Wang (Biometrics, 1999), Lehmacher and Wassmer (Biometrics, 1999), and Müller and Schäfer (Biometrics, 2001). However, corresponding solutions for the equally important and related problem of parameter estimation at the end ...
Gao, Ping, Liu, Lingyun, Mehta, Cyrus
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A unified framework for weighted parametric group sequential design

Biometrical Journal, 2022
AbstractGroup sequential design (GSD) is widely used in clinical trials in which correlated tests of multiple hypotheses are used. Multiple primary objectives resulting in tests with known correlations include evaluating (1) multiple experimental treatment arms, (2) multiple populations, (3) the combination of multiple arms and multiple populations, or
Keaven M. Anderson, Zifang Guo, Jing Zhao, Linda Z. Sun   +3 more
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Computation of optimal group sequential designs

Sequential Analysis, 2016
ABSTRACTWe propose a method of simulation to compute optimal group sequential tests that minimize the average sample size and meet significance level and power requirements. Optimal designs can be used in clinical trials directly, and provide a standard for assessing the efficiency of other designs as well.
Qi An, Myron Chang
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Group Sequential Design With Change of Endpoint

Statistics in Biopharmaceutical Research, 2017
In Rheumatoid Arthritis studies, scientists usually need to focus on multiple endpoints simultaneously. Regulatory agencies require ACR20 as the primary endpoint for approval and making decisions.
Lulu Wang, Qing Li, Ziliang Li, Amarjot Kaur   +3 more
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Designing complex group sequential survival trials

Statistics in Medicine, 2002
AbstractThis paper presents methodology for designing complex group sequential survival trials when the survival curves will be compared using the logrank statistic. The method can be applied to any treatment and control survival curves as long as each hazard function can be approximated by a piecewise linear function.
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Nonparametric Bayesian Group Sequential Design

1998
The customary objective of a group sequential design is the comparison of several treatments or populations. The evolutionary nature of such trials encourages the use of the Bayesian paradigm in the design, monitoring and analysis of these trials. Here we focus on the design issue for the case of continuous, possibly multivariate response at each trial.
Pantelis K. Vlachos, Alan E. Gelfand
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A Simple Algorithm for Designing Group Sequential Clinical Trials

Biometrics, 2001
This article describes a simple algorithm for calculating probabilities associated with group sequential trials. This allows the choice of boundaries that may not be among those implemented in available software.
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