A practical guide to understanding Kaplan-Meier curves

Author:

Rich Jason T.1,Neely J. Gail1,Paniello Randal C.1,Voelker Courtney C. J.1,Nussenbaum Brian1,Wang Eric W.1

Affiliation:

1. From the Department of Otolaryngology-Head and Neck Surgery, Washington University School of Medicine, St. Louis, MO.

Abstract

In 1958, Edward L. Kaplan and Paul Meier collaborated to publish a seminal paper on how to deal with incomplete observations. Subsequently, the Kaplan-Meier curves and estimates of survival data have become a familiar way of dealing with differing survival times (times-to-event), especially when not all the subjects continue in the study. “Survival” times need not relate to actual survival with death being the event; the “event” may be any event of interest. Kaplan-Meier analyses are also used in nonmedical disciplines. The purpose of this article is to explain how Kaplan-Meier curves are generated and analyzed. Throughout this article, we will discuss Kaplan-Meier estimates in the context of “survival” before the event of interest. Two small groups of hypothetical data are used as examples in order for the reader to clearly see how the process works. These examples also illustrate the crucially important point that comparative analysis depends upon the whole curve and not upon isolated points. © 2010 American Academy of Otolaryngology-Head and Neck Surgery Foundation. All rights reserved.

Publisher

SAGE Publications

Subject

Otorhinolaryngology,Surgery

Reference5 articles.

1. Nonparametric Estimation from Incomplete Observations

2. Altman DG. Practical Statistics for Medical Research. New York: Chapman & Hall/CRC; 1991. p. 365–96.

3. Feinstein AR. Clinical Epidemiology: The Architecture of Clinical Research. Philadelphia: W. B. Saunders Co.; 1985. p. 226–7, 335,343–6.

4. Survival of Patients with Stage I Lung Cancer Detected on CT Screening

5. Cautionary Note Regarding the Use of CIs Obtained From Kaplan-Meier Survival Curves

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