“Statistical Considerations on the Process of Discovering and Validating Biomarker Candidates Using Mass Spectrometry Platforms”
DATE: May 25, 2007
TIME: 3:00 PM – 4:00 PM
SPEAKER: Cliff Spiegelman, Ph.D., Professor of Statistics, Texas A & M University
LOCATION: Northwestern University (Evanston Campus), CBC Cook Hall Access Grid Site, Cook Hall, Room: 3118, 2220 Campus Drive, Evanston
ABSTRACT: Claims have been made that the application of supervised pattern recognition methodology can be used with mass spectrometry (MS) proteomic data to achieve near perfect sensitivity and specificity for detecting early stage cancer. So far those claims have not been verified partly due to the use of less than optimal experimental design. In the interim significant effort has been spent on proteomic biomarker discovery research (without significant positive results) largely using tandem MS platforms. Underpinning the proteomics studies are several key components including standardization of materials, bioinformatics, reagent development, MS improvements, and statistics. This presentation discusses the National Cancer Institute’s Clinical Proteomic Technology Assessment for Cancer and a related study, focusing on the statistical design of experiment input.