title: The analysis of survival data in nephrology: basic concepts and methods of Cox regression.
abstract: How much does the survival of one group differ from the survival of another group? How do differences in age in these two groups affect such a comparison? To obtain a quantity to compare the survival of different patient groups and to account for confounding effects, a multiple regression technique for survival data is needed. Cox regression is perhaps the most popular regression technique for survival analysis. This paper explains how Cox regression works, what the proportionality assumption means and how to interpret the results of univariate and multiple Cox regression models.
authors.affiliation: Department of Medical Informatics, ERA-EDTA Registry, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands.
authors.forename: Paul C
authors.initials: PC
authors.lastname: van Dijk
authors.forename: Kitty J
authors.initials: KJ
authors.lastname: Jager
authors.forename: Aeilko H
authors.initials: AH
authors.lastname: Zwinderman
authors.forename: Carmine
authors.initials: C
authors.lastname: Zoccali
authors.forename: Friedo W
authors.initials: FW
authors.lastname: Dekker
mesh_terms: D003920:Diabetes Mellitus / Q000401:mortality; D006801:Humans; D007676:Kidney Failure, Chronic / Q000401:mortality; D009398:Nephrology / Q000379:methods*; D016016:Proportional Hazards Models; D016019:Survival Analysis