Dose-Finding Designs for Phase I Clinical Trials in Oncology and Use of Selective Phenotypying to Increase Power of Genetic Association Studies

• Activity Number: 293
• Type: Contributed
• Date/Time: Tuesday, August 5, 2014 : 8:30 AM to 10:20 AM
• Sponsor: Biopharmaceutical Section
• Author(s): Yunfei Wang*+ and Ethan M. Lange
• Companies: Children's National Medical Center and University of North Carolina
• Keywords: power ; biomarkers ; simulated annealing ; selective phenotype

Abstract

Blood-based biomarkers and other quantitative measures can provide valuable insights into disease etiology and are often used as intermediate outcomes for identifying risk factors associated with disease. Genome-wide association studies (GWAS) between quantitative traits and single-nucleotide polymorphisms (SNPs) are routinely performed on large samples from population-based cohorts. Replication studies are an important step in controlling the type I error rate of reported GWAS findings. Many potential replication cohorts have existing genome-wide SNP data but have not yet measured the quantitative trait of interest. Measuring these traits can be expensive and time consuming, which can deter studies from pursuing replication. Given the expense and time of measuring these quantitative traits on large samples, it would be desirable to identify a subset of subjects that could be phenotyped to optimize statistical power under fixed sample size constraints. We describe an approach of utilizing existing genotype data to identify an optimal subset of samples to be phenotyped and included in a genetic replication study. Specifically, we have developed a simulated annealing-based algori