title: A copula approach for detecting prognostic genes associated with survival outcome in microarray studies.
abstract: A challenging and crucial issue in clinical studies in cancer involving gene microarray experiments is the discovery, among a large number of genes, of a relatively small panel of genes whose elements are associated with a relevant clinical outcome variable such as time-to-death or time-to-recurrence of disease. A semiparametric approach, using dependence functions known as copulas, is considered to quantify and estimate the pairwise association between the outcome and each gene expression. These time-to-event type endpoints are typically subject to censoring as not all events are realized at the time of the analysis. Furthermore, given that the total number of genes is typically large, it is imperative to control a relevant error rate in any gene discovery procedure. The proposed method addresses the two aforementioned issues by direct incorporation of the censoring mechanism and by appropriate statistical adjustment for multiplicity. The performance of the proposed method is studied through simulation and illustrated with an application using a case study in lung cancer.
authors.affiliation: Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, North Carolina 27705, USA. kouros.owzar@duke.edu
authors.forename: Kouros
authors.initials: K
authors.lastname: Owzar
authors.forename: Sin-Ho
authors.initials: SH
authors.lastname: Jung
authors.forename: Pranab Kumar
authors.initials: PK
authors.lastname: Sen
mesh_terms: D014408:Biomarkers, Tumor / Q000032:analysis*; D003627:Data Interpretation, Statistical; D020869:Gene Expression Profiling / Q000379:methods; D006801:Humans; D009363:Neoplasm Proteins / Q000032:analysis*; D009369:Neoplasms / Q000378:metabolism* / Q000401:mortality*; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D011379:Prognosis; D016019:Survival Analysis; D015996:Survival Rate
chemical_list: D014408:Biomarkers, Tumor; D009363:Neoplasm Proteins