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Abstract Details
Activity Number:
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667
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Type:
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Contributed
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Date/Time:
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Thursday, August 4, 2011 : 10:30 AM to 12:20 PM
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Sponsor:
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Biopharmaceutical Section
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Abstract - #300687 |
Title:
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Does Meta-Regression Have Enough Power? An Empirical Study of 500 Meta-Analyses of Randomized Controlled Trials
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Author(s):
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Stephanie Ann Kovalchik*+
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Companies:
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University of California at Los Angeles
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Address:
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skoval@ucla.edu, Los Angeles, CA, 91106, USA
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Keywords:
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meta-analysis ;
meta-regression ;
subgroup analysis ;
effect modifier ;
randomized controlled trials
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Abstract:
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When assessing treatment interventions, meta-analysts are interested in using meta-regression to identify subgroups of patients with a different treatment response. Simulation studies have suggested that, owing to loss of within-study information, meta-regression might not have sufficient power to detect covariate-treatment interactions for patient-defined covariates. To determine whether this generally holds for current quantitative reviews, I assessed the power of meta-regression for 500 recently published meta-analyses of randomized controlled trials, considering a range of subgroup scenarios--varying ratio of within- to between-study information. In each case, comparison was made to the power of an individual patient data (IPD) analysis. I also summarize the findings from a survey of meta-analysts on the process and success of collecting IPD. Implications for future multitrial subgroup analyses are discussed.
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The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.
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