title: Issues in developing multivariable molecular signatures for guiding clinical care decisions.
abstract: Omics technologies that generate a large amount of molecular data characterizing biospecimens have the potential to provide information about patients' disease characteristics above and beyond standard clinical features. By combining information from a large number of features into a multivariable model, called a biomarker signature, there is the opportunity to identify distinct subgroups of patients for whom treatment decisions can be personalized. The key challenge is to derive a signature with good performance and appropriately characterize its performance. We summarize the key statistical issues and methods for developing and validating biomarker signatures, using examples from the literature for illustration.
authors: a Biostatistics Branch, Biometric Research Program , National Cancer Institute , Bethesda , Maryland , USA.
authors: Michael C
authors: MC
authors: Sachs
authors: a Biostatistics Branch, Biometric Research Program , National Cancer Institute , Bethesda , Maryland , USA.
authors: Lisa M
authors: LM
authors: McShane
mesh_terms: D015415:Biomarkers / Q000032:analysis*; D000066491:Clinical Decision-Making; D006801:Humans; D015233:Models, Statistical; D015999:Multivariate Analysis
chemical_list: D015415:Biomarkers
keywords: Biomarkers; biomarker signatures; personalized medicine