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

被引:31
作者
Samar Abd ElHafeez
Claudia Torino
Graziella D’Arrigo
Davide Bolignano
Fabio Provenzano
Francesco Mattace-Raso
Carmine Zoccali
Giovanni Tripepi
机构
[1] Clinical Epidemiology and Physiopathology of Renal Diseases and Hypertension of Reggio Calabria,CNR
[2] Erasmus Medical Center of Rotterdam,IBIM
关键词
Cox regression analysis; Kaplan-Meier analysis; survival analysis;
D O I
10.1007/BF03325249
中图分类号
学科分类号
摘要
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.
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页码:203 / 206
页数:3
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