title: Survival analysis II: Cox regression.
abstract: In contrast to the Kaplan-Meier method, Cox proportional hazards regression can provide an effect estimate by quantifying the difference in survival between patient groups and can adjust for confounding effects of other variables. The purpose of this article is to explain the basic concepts of the Cox regression method, and to provide some guidance regarding the presentation of the results.
authors.affiliation: ERA-EDTA Registry, Department of Medical Informatics, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands. v.s.stel@amc.uva.nl
authors.forename: Vianda S
authors.initials: VS
authors.lastname: Stel
authors.forename: Friedo W
authors.initials: FW
authors.lastname: Dekker
authors.forename: Giovanni
authors.initials: G
authors.lastname: Tripepi
authors.forename: Carmine
authors.initials: C
authors.lastname: Zoccali
authors.forename: Kitty J
authors.initials: KJ
authors.lastname: Jager
mesh_terms: D016001:Confidence Intervals; D003627:Data Interpretation, Statistical; D005919:Glomerular Filtration Rate; D006801:Humans; D007674:Kidney Diseases / Q000401:mortality*; D016016:Proportional Hazards Models