Gene selection in microarray survival studies under possibly non-proportional hazards | Zendy

Daniela Dunkler | Zendy; M. Schemper | Zendy; Georg Heinze | Zendy

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Gene selection in microarray survival studies under possibly non-proportional hazards

Author(s) -

Daniela Dunkler,

M. Schemper,

Georg Heinze

Publication year - 2010

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btq035

Subject(s) - proportional hazards model , censoring (clinical trials) , gene selection , univariate , statistics , concordance , regression , regression analysis , survival analysis , covariate , log rank test , linear regression , multivariate statistics , gene , mathematics , computer science , computational biology , biology , microarray analysis techniques , bioinformatics , genetics , gene expression

Univariate Cox regression (COX) is often used to select genes possibly linked to survival. With non-proportional hazards (NPH), COX could lead to under- or over-estimation of effects. The effect size measure c=P(T(1)<T(0)), i.e. the probability that a person randomly chosen from group G(1) dies earlier than a person from G(0), is independent of the proportional hazards (PH) assumption. Here we consider its generalization to continuous data c' and investigate the suitability of c' for gene selection.

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