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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

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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.

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Authors and Affiliations

  1. CNR-IBIM, Clinical Epidemiology and Physiopathology of Renal Diseases and Hypertension of Reggio Calabria, c/o Euroline of Ascrizzi Vincent, Via Vallone Petrara 55/57, 89124, Reggio Calabria, Italy

    Samar Abd ElHafeez, Claudia Torino, Graziella D’Arrigo, Davide Bolignano, Fabio Provenzano, Carmine Zoccali &  Giovanni Tripepi

  2. Department of Geriatric and Internal Medicine, Erasmus Medical Center of Rotterdam, The Netherlands

    Francesco Mattace-Raso

Authors
  1. Samar Abd ElHafeez
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  2. Claudia Torino
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  3. Graziella D’Arrigo
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  4. Davide Bolignano
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  5. Fabio Provenzano
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  6. Francesco Mattace-Raso
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  7. Carmine Zoccali
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  8. Giovanni Tripepi
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Corresponding author

Correspondence to Giovanni Tripepi.

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ElHafeez, S.A., Torino, C., D’Arrigo, G. et al. 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. Aging Clin Exp Res 24, 203–206 (2012). https://doi.org/10.1007/BF03325249

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  • DOI: https://doi.org/10.1007/BF03325249

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