Analyzing survival curves at a fixed point in time.
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.
Klein
John P
JP
Division of Biostatistics, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI 53226, USA. klein@mcw.edu
Logan
Brent
B
Harhoff
Mette
M
Andersen
Per Kragh
PK
D016026:Bone Marrow Transplantation; D018572:Disease-Free Survival; D006801:Humans; D053208:Kaplan-Meier Estimate; D007938:Leukemia / Q000401:mortality / Q000628:therapy; D016014:Linear Models; D015233:Models, Statistical; D009010:Monte Carlo Method; D013997:Time Factors; D014182:Transplantation, Autologous; D014184:Transplantation, Homologous