Volume 26, Issue 24
Research Article

Analyzing survival curves at a fixed point in time

John P. Klein

Corresponding Author

E-mail address: klein@mcw.edu

Division of Biostatistics, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI 53226, U.S.A.

Division of Biostatistics, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI 53226, U.S.A.Search for more papers by this author
Brent Logan

Division of Biostatistics, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI 53226, U.S.A.

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Mette Harhoff

Department of Biostatistics, University of Copenhagen, Ø. Farimagsgade 5, PB 2099, DK 1014 Copenhagen K, Denmark

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Per Kragh Andersen

Department of Biostatistics, University of Copenhagen, Ø. Farimagsgade 5, PB 2099, DK 1014 Copenhagen K, Denmark

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First published: 09 March 2007
Citations: 144

Abstract

A common problem encountered in many medical applications is the comparison of survival curves. Often, rather than comparison of the entire survival curves, interest is focused on the comparison at a fixed point in time. In most cases, the naive test based on a difference in the estimates of survival is used for this comparison. In this note, we examine the performance of alternatives to the naive test. These include tests based on a number of transformations of the survival function and a test based on a generalized linear model for pseudo‐observations. The type I errors and power of these tests for a variety of sample sizes are compared by a Monte Carlo study. We also discuss how these tests may be extended to situations where the data are stratified. The pseudo‐value approach is also applicable in more detailed regression analysis of the survival probability at a fixed point in time. The methods are illustrated on a study comparing survival for autologous and allogeneic bone marrow transplants. Copyright © 2007 John Wiley & Sons, Ltd.

Number of times cited according to CrossRef: 144

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