"Omics" data and levels of evidence for biomarker discovery.
With the development of new technologies for assaying biological activity on a global basis in experimental samples, various new "-omics" signatures have been developed to predict disease progression. Such signatures hold the potential to alter the nature of clinical management of human disease. In this article, we describe some necessary statistical considerations needed to take these signatures from the discovery phase to a clinically useful assay. Much of the work discussed is in the area of cancer.
Ghosh
Debashis
D
Department of Statistics, College of Medicine, Pennsylvania State University, University Park, PA 16802, USA. ghoshd@psu.edu
Poisson
Laila M
LM
D014408:Biomarkers, Tumor / Q000378:metabolism*; D016022:Case-Control Studies; D019295:Computational Biology / Q000379:methods*; D003627:Data Interpretation, Statistical; D018450:Disease Progression; D006801:Humans; D009369:Neoplasms / Q000378:metabolism* / Q000503:physiopathology; D040901:Proteomics; D016032:Randomized Controlled Trials as Topic
D014408:Biomarkers, Tumor