title: An overview on standard statistical methods for assessing exposure-outcome link in survival analysis (Part II): the Kaplan-Meier analysis and the Cox regression method.
abstract: The Kaplan-Meier and the Cox regression methods are the most used statistical techniques for performing "time to event analysis" in epidemiological and clinical research. The Kaplan-Meier analysis allows to build up one or more survival curves describing the occurrence of the outcome of interest over time according to the presence/absence of one or more exposures. The Cox regression method models the relationship between a specific exposure (either a continuous one like age, and systolic blood pressure or a categorical one like diabetes, degree of obesity, etc.) and the occurrence of a given outcome taking into account multiple confounders and/or predictors.
authors.affiliation: CNR-IBIM, Clinical Epidemiology and Physiopathology of Renal Diseases and Hypertension of Reggio Calabria, Italy.
authors.forename: Samar
authors.initials: S
authors.lastname: Abd ElHafeez
authors.forename: Claudia
authors.initials: C
authors.lastname: Torino
authors.forename: Graziella
authors.initials: G
authors.lastname: D'Arrigo
authors.forename: Davide
authors.initials: D
authors.lastname: Bolignano
authors.forename: Fabio
authors.initials: F
authors.lastname: Provenzano
authors.forename: Francesco
authors.initials: F
authors.lastname: Mattace-Raso
authors.forename: Carmine
authors.initials: C
authors.lastname: Zoccali
authors.forename: Giovanni
authors.initials: G
authors.lastname: Tripepi
mesh_terms: D006801:Humans; D053208:Kaplan-Meier Estimate; D017063:Outcome Assessment, Health Care; D016016:Proportional Hazards Models; D012044:Regression Analysis; D016019:Survival Analysis; D013997:Time Factors