We have located links that may give you full text access.
JOURNAL ARTICLE
REVIEW
An unjustified benefit: immortal time bias in the analysis of time-dependent events.
Transplant International 2018 Februrary
Immortal time bias is a problem arising from methodologically wrong analyses of time-dependent events in survival analyses. We illustrate the problem by analysis of a kidney transplantation study. Following patients from transplantation to death, groups defined by the occurrence or nonoccurrence of graft failure during follow-up seemingly had equal overall mortality. Such naive analysis assumes that patients were assigned to the two groups at time of transplantation, which actually are a consequence of occurrence of a time-dependent event later during follow-up. We introduce landmark analysis as the method of choice to avoid immortal time bias. Landmark analysis splits the follow-up time at a common, prespecified time point, the so-called landmark. Groups are then defined by time-dependent events having occurred before the landmark, and outcome events are only considered if occurring after the landmark. Landmark analysis can be easily implemented with common statistical software. In our kidney transplantation example, landmark analyses with landmarks set at 30 and 60 months clearly identified graft failure as a risk factor for overall mortality. We give further typical examples from transplantation research and discuss strengths and limitations of landmark analysis and other methods to address immortal time bias such as Cox regression with time-dependent covariables.
Full text links
Related Resources
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app
All material on this website is protected by copyright, Copyright © 1994-2024 by WebMD LLC.
This website also contains material copyrighted by 3rd parties.
By using this service, you agree to our terms of use and privacy policy.
Your Privacy Choices
You can now claim free CME credits for this literature searchClaim now
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app