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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
biochemistry, genetics and molecular biology
Statistical design for biospecimen cohort size in proteomics-based biomarker discovery and verification studies
Journal of Proteome Research, Volume 12, No. 12, Year 2013
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Description
Protein biomarkers are needed to deepen our understanding of cancer biology and to improve our ability to diagnose, monitor, and treat cancers. Important analytical and clinical hurdles must be overcome to allow the most promising protein biomarker candidates to advance into clinical validation studies. Although contemporary proteomics technologies support the measurement of large numbers of proteins in individual clinical specimens, sample throughput remains comparatively low. This problem is amplified in typical clinical proteomics research studies, which routinely suffer from a lack of proper experimental design, resulting in analysis of too few biospecimens to achieve adequate statistical power at each stage of a biomarker pipeline. To address this critical shortcoming, a joint workshop was held by the National Cancer Institute (NCI), National Heart, Lung, and Blood Institute (NHLBI), and American Association for Clinical Chemistry (AACC) with participation from the U.S. Food and Drug Administration (FDA). An important output from the workshop was a statistical framework for the design of biomarker discovery and verification studies. Herein, we describe the use of quantitative clinical judgments to set statistical criteria for clinical relevance and the development of an approach to calculate biospecimen sample size for proteomic studies in discovery and verification stages prior to clinical validation stage. This represents a first step toward building a consensus on quantitative criteria for statistical design of proteomics biomarker discovery and verification research. © 2013 American Chemical Society.
Authors & Co-Authors
Skates, Steven James
United States, Boston
Massachusetts General Hospital Cancer Center
Gillette, Michael A.
United States, Cambridge
Massachusetts Institute of Technology
LaBaer, Joshua L.
United States, Tempe
Arizona State University
Carr, Steven Alfred
United States, Cambridge
Massachusetts Institute of Technology
Anderson, Leigh
United States, Washington, D.c.
The Plasma Proteome Institute
United States, Washington, D.c.
Siscapa Assay Technologies, Inc
Liebler, Daniel C.
United States, Nashville
Vanderbilt University
Ransohoff, David F.
United States, Chapel Hill
The University of North Carolina at Chapel Hill
Rifai, Nader
United States, Boston
Boston Children's Hospital
United States, Boston
Harvard Medical School
Saudi Arabia, Jeddah
King Abdulaziz University
Kondratovich, Marina V.
United States, Rockville
Food and Drug Administration, Center for Devices and Radiological Health
Težak, Živana
United States, Rockville
Food and Drug Administration, Center for Devices and Radiological Health
Mansfield, Elizabeth A.
United States, Rockville
Food and Drug Administration, Center for Devices and Radiological Health
Oberg, Ann L.
United States, Rochester
Mayo Clinic
Wright, Ian
United States, Washington, D.c.
Siscapa Assay Technologies, Inc
Barnes, Grady
Japan, Tokyo
Fujirebio Inc.
Gail, Mitchell H.
United States, Rockville
National Cancer Institute Nci
Mesri, Mehdi
United States, Rockville
National Cancer Institute Nci
Kinsinger, Christopher R.
United States, Rockville
National Cancer Institute Nci
Rodriguez, Henry F.
United States, Rockville
National Cancer Institute Nci
Boja, Emily S.
United States, Rockville
National Cancer Institute Nci
Statistics
Citations: 102
Authors: 19
Affiliations: 14
Identifiers
Doi:
10.1021/pr400132j
ISSN:
15353893
e-ISSN:
15353907
Research Areas
Cancer
Food Security
Study Design
Cohort Study
Study Approach
Quantitative