Linked Life Data

19152230

Source:http://linkedlifedata.com/resource/pubmed/id/19152230

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
5
pubmed:dateCreated
2009-2-4
pubmed:abstractText
The log-rank test is the most powerful non-parametric test for detecting a proportional hazards alternative and thus is the most commonly used testing procedure for comparing time-to-event distributions between different treatments in clinical trials. When the log-rank test is used for the primary data analysis, the sample size calculation should also be based on the test to ensure the desired power for the study. In some clinical trials, the treatment effect may not manifest itself right after patients receive the treatment. Therefore, the proportional hazards assumption may not hold. Furthermore, patients may discontinue the study treatment prematurely and thus may have diluted treatment effect after treatment discontinuation. If a patient's treatment termination time is independent of his/her time-to-event of interest, the termination time can be treated as a censoring time in the final data analysis. Alternatively, we may keep collecting time-to-event data until study termination from those patients who discontinued the treatment and conduct an intent-to-treat analysis by including them in the original treatment groups. We derive formulas necessary to calculate the asymptotic power of the log-rank test under this non-proportional hazards alternative for the two data analysis strategies. Simulation studies indicate that the formulas provide accurate power for a variety of trial settings. A clinical trial example is used to illustrate the application of the proposed methods.
pubmed:grant
pubmed:commentsCorrections
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Feb
pubmed:issn
0277-6715
pubmed:author
pubmed:copyrightInfo
Copyright (c) 2009 John Wiley & Sons, Ltd.
pubmed:issnType
Print
pubmed:day
28
pubmed:volume
28
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
864-79
pubmed:dateRevised
2010-12-3
pubmed:meshHeading
pubmed:year
2009
pubmed:articleTitle
Power and sample size calculation for log-rank test with a time lag in treatment effect.
pubmed:affiliation
Department of Statistics, North Carolina State University, Raleigh, NC 27695-8203, U.S.A. dzhang2@stat.ncsu.edu
pubmed:publicationType
Journal Article, Research Support, N.I.H., Extramural