Faculty Collaboration Database

Analyzing survival curves at a fixed point in time. Stat Med 2007 Oct 30;26(24):4505-19

Date

03/10/2007

Pubmed ID

17348080

DOI

10.1002/sim.2864

Scopus ID

2-s2.0-35148838428 (requires institutional sign-in at Scopus site)   276 Citations

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.

Author List

Klein JP, Logan B, Harhoff M, Andersen PK

Author

Brent R. Logan PhD Director, Professor in the Data Science Institute department at Medical College of Wisconsin

MESH terms used to index this publication - Major topics in bold

Bone Marrow Transplantation
Disease-Free Survival
Humans
Kaplan-Meier Estimate
Leukemia
Linear Models
Models, Statistical
Monte Carlo Method
Time Factors
Transplantation, Autologous
Transplantation, Homologous