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Abstract Details

Activity Number: 572
Type: Contributed
Date/Time: Wednesday, August 1, 2012 : 2:00 PM to 3:50 PM
Sponsor: Biopharmaceutical Section
Abstract - #304144
Title: Testing CV Effects Using Ultrasound Imaging Biomarkers
Author(s): Shubing Wang*+
Companies: Merck
Address: 126 East Lincoln Avenue, Rahway, NJ, 07065, United States
Keywords: Cardiovascular ; preclinical ; ultrasound imaging ; cell-mean

Advances in technology leads to faster and more accurate acquisition of ultrasound imaging biomarkers, which make ultrasound imaging one of the standard platforms of the testing Cardiovascular (CV) effects in the preclinical trails. The challenges of the statistical analysis of ultrasound imaging biomarkers present in the following aspects: 1) the biomarkers are not randomized at the baseline; 2) the percents of missing data is high; 3) many biomarkers are scanned at the same time points; 4) the searching of "leading biomarkers" causes multiplicity problems. We design a completely automated system by implementing a cell-mean mixed effects model which deals with the non-randomized baselines, effectively handles missing data issues, processes multiple biomarkers in a batch model, and applies False Discover Rate (FDR) method handling multiplicity adjustments.

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