Abstract Details
Activity Number:
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486
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Type:
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Contributed
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Date/Time:
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Wednesday, August 7, 2013 : 8:30 AM to 10:20 AM
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Sponsor:
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Biopharmaceutical Section
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Abstract - #308535 |
Title:
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Inference from Blinded Data in Randomized Clinical Trials
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Author(s):
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Kefei Zhou*+ and Jeetu Ganju
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Companies:
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Amgen. Co and Gilead
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Keywords:
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adaptive trials ;
randomization block size ;
sample size re-estimation
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Abstract:
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With blinded data the consensus is that there is a negligible chance of inferring a non-null treatment effect. The recent FDA draft guidance document on adaptive trials implicitly shares this commonly held view. A re-examination shows that for superiority trials the probability of gleaning a signal from the noise in the blinded data is not as trivial as claimed for continuous endpoints. The probability, while small, is much larger than previously thought and seems large enough to re-evaluate the consensus view. Development of a covariate-adjusted statistic permitting more aggressive modeling of blinded data is a major contributor in improving signal detection. Other contributing factors include some complementary ad hoc analysis methods and overpowered trials for reasons external to powering the primary objective. The methods described are better suited for superiority trials than for non-inferiority or equivalence trials. Two examples illustrate the performance of the blinded methods.
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Authors who are presenting talks have a * after their name.
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