%0 Journal Article %1 Klein2007 %A Klein, John P %A Logan, Brent %A Harhoff, Mette %A Andersen, Per Kragh %D 2007 %J Statistics in medicine %K Autologous BoneMarrowTransplantation Disease-FreeSurvival Homologous Humans Kaplan-MeierEstimate Leukemia Leukemia:mortality Leukemia:therapy LinearModels Models MonteCarloMethod Statistical TimeFactors Transplantation %N 24 %P 4505-19 %R 10.1002/sim.2864 %T Analyzing survival curves at a fixed point in time. %U http://www.ncbi.nlm.nih.gov/pubmed/17348080 %V 26 %X 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. %@ 0277-6715

@article{Klein2007, 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.}, added-at = {2023-02-03T11:44:35.000+0100}, author = {Klein, John P and Logan, Brent and Harhoff, Mette and Andersen, Per Kragh}, biburl = {https://www.bibsonomy.org/bibtex/23cd9d33200240ee3734dd134c09edf2d/jepcastel}, city = {Division of Biostatistics, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI 53226, USA. klein@mcw.edu}, doi = {10.1002/sim.2864}, interhash = {636825bf9cbd4d491e8774919981530f}, intrahash = {3cd9d33200240ee3734dd134c09edf2d}, isbn = {0277-6715}, issn = {0277-6715}, journal = {Statistics in medicine}, keywords = {Autologous BoneMarrowTransplantation Disease-FreeSurvival Homologous Humans Kaplan-MeierEstimate Leukemia Leukemia:mortality Leukemia:therapy LinearModels Models MonteCarloMethod Statistical TimeFactors Transplantation}, month = {10}, note = {4622<m:linebreak></m:linebreak>CI: Copyright (c) 2007; GR: R01 CA54706-10/CA/NCI NIH HHS/United States; JID: 8215016; ppublish;<m:linebreak></m:linebreak>Anàlisi de supervivència}, number = 24, pages = {4505-19}, pmid = {17348080}, timestamp = {2023-02-03T11:44:35.000+0100}, title = {Analyzing survival curves at a fixed point in time.}, url = {http://www.ncbi.nlm.nih.gov/pubmed/17348080}, volume = 26, year = 2007 }