Abstract Details
Activity Number:
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60
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Type:
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Topic Contributed
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Date/Time:
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Sunday, August 4, 2013 : 4:00 PM to 5:50 PM
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Sponsor:
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Section on Statistical Learning and Data Mining
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Abstract - #308119 |
Title:
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A Resampling-based Ensemble Tree Method to Identify Patient Subgroups with Enhanced Treatment Effect
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Author(s):
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Chakib Battioui*+ and Lei Shen and Stephen J. Ruberg
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Companies:
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Eli Lilly & Company and Eli Lilly & Company and Eli Lilly & Company
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Keywords:
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Tailored Therapeutics ;
Predictive Biomarkers ;
Multiplicity ;
Subgroup Identification
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Abstract:
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In this paper we describe an approach to identify patient subgroups with enhanced treatment effect in clinical trials. It utilizes ensemble trees based on resampling and naturally produces two consistency measures for each potential subgroup identified. We compare simple ways to combine these measures into an overall summary of strength. Using stratified permutations and out-of-bag samples, the approach also provides a multiplicity-adjusted p-value and bias-corrected estimate of treatment effect, both of which are important for decision-making in tailored therapeutics applications. A simulation study is performed to evaluate the performance of the proposed method.
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Authors who are presenting talks have a * after their name.
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