The analysis of survival data in nephrology: basic concepts and methods of Cox regression | Zendy

Paul C. van Dijk | Zendy; Kitty J. Jager | Zendy; Aeilko H. Zwinderman | Zendy; Carmine Zoccali | Zendy; Friedo W. Dekker | Zendy

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The analysis of survival data in nephrology: basic concepts and methods of Cox regression

Author(s) -

Paul C. van Dijk,

Kitty J. Jager,

Aeilko H. Zwinderman,

Carmine Zoccali,

Friedo W. Dekker

Publication year - 2008

Publication title -

kidney international

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.499

H-Index - 276

eISSN - 1523-1755

pISSN - 0085-2538

DOI - 10.1038/ki.2008.294

Subject(s) - proportional hazards model , nephrology , medicine , survival analysis , regression analysis , regression , oncology , statistics , mathematics

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.

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