Advertisement

Survival Analysis

  • Bryan Kestenbaum
Chapter

Abstract

Survival analysis is used to describe the continuous probability of disease-free survival over follow-up. The survivor function, S(t), is a function fit to the study data that returns the cumulative probability of being free of the outcome at a particular time. The Kaplan-Meier method is used to estimate S(t) in the presence of censoring, which is defined as leaving a study for any reason before incurring the outcome of interest. Kaplan-Meier plots are useful for estimating time-specific survival among one or more study groups. The Cox proportional hazards model yields a measure of risk called the hazard ratio, which represents an average relative risk over a specified period of follow-up time.

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Bryan Kestenbaum
    • 1
  1. 1.Division of Nephrology, Department of MedicineUniversity of WashingtonSeattleUSA

Personalised recommendations