Abstract Details
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Activity Number:
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394
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Type:
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Contributed
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Date/Time:
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Tuesday, August 5, 2014 : 2:00 PM to 3:50 PM
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Sponsor:
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Biopharmaceutical Section
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Abstract #311692
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View Presentation
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Title:
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Bayesian Predictive Probability Approach for Phase III Success Based on Published Trial Results from Early Development
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Author(s):
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Meichun Ding*+ and Ying Yang
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Companies:
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GlaxoSmithKline and FDA/CDRH
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Keywords:
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Bayesian Predictive Probability
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Abstract:
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Often in Oncology the relationship between surrogate endpoints and overall survival are of special interest to guide front loading activities in drug development strategy plans of clinical trials. This abstract describes an approach of predicting phase III success of overall survival as primary endpoint utilizing published phase II results with surrogate endpoints by utilizing a Bayesian predictive probability approach. A special case in an AML indication is discussed in which indications are mixed and there are limited randomized trial results currently reported.
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Authors who are presenting talks have a * after their name.
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