Many analyses of observational data are attempts to emulate a target trial. The emulation of the target trial may fail when researchers deviate from simple principles that guide the design and analysis of randomized experiments. We review a framework to describe and prevent biases, including immortal time bias, that result from a failure to align start of follow-up, specification of eligibility, and treatment assignment. We review some analytic approaches to avoid these problems in comparative effectiveness or safety research.
%0 Journal Article
%1 Hernan2016
%A Hernán, Miguel A
%A Sauer, Brian C
%A Hernández-Díaz, Sonia
%A Platt, Robert
%A Shrier, Ian
%D 2016
%J Journal of clinical epidemiology
%K Comparativeeffectivenessresearch Immortaltimebias Observational Selectionbias Targettrial Timezero studies
%P 70-75
%R 10.1016/j.jclinepi.2016.04.014
%T Specifying a target trial prevents immortal time bias and other self-inflicted injuries in observational analyses.
%U http://linkinghub.elsevier.com/retrieve/pii/S0895435616301366 http://www.ncbi.nlm.nih.gov/pubmed/27237061 http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC5124536
%V 79
%X Many analyses of observational data are attempts to emulate a target trial. The emulation of the target trial may fail when researchers deviate from simple principles that guide the design and analysis of randomized experiments. We review a framework to describe and prevent biases, including immortal time bias, that result from a failure to align start of follow-up, specification of eligibility, and treatment assignment. We review some analytic approaches to avoid these problems in comparative effectiveness or safety research.
@article{Hernan2016,
abstract = {Many analyses of observational data are attempts to emulate a target trial. The emulation of the target trial may fail when researchers deviate from simple principles that guide the design and analysis of randomized experiments. We review a framework to describe and prevent biases, including immortal time bias, that result from a failure to align start of follow-up, specification of eligibility, and treatment assignment. We review some analytic approaches to avoid these problems in comparative effectiveness or safety research.},
added-at = {2023-02-03T11:44:35.000+0100},
author = {Hernán, Miguel A and Sauer, Brian C and Hernández-Díaz, Sonia and Platt, Robert and Shrier, Ian},
biburl = {https://www.bibsonomy.org/bibtex/251a7f3ec1b4df7d35f16ced2cc205f9c/jepcastel},
doi = {10.1016/j.jclinepi.2016.04.014},
interhash = {eca8259c846d2eb1f195cd588d32c2ed},
intrahash = {51a7f3ec1b4df7d35f16ced2cc205f9c},
issn = {1878-5921},
journal = {Journal of clinical epidemiology},
keywords = {Comparativeeffectivenessresearch Immortaltimebias Observational Selectionbias Targettrial Timezero studies},
month = {11},
note = {Mesures d'associació; Observacionals; Immortal time bias; CER},
pages = {70-75},
pmid = {27237061},
timestamp = {2023-02-03T11:44:35.000+0100},
title = {Specifying a target trial prevents immortal time bias and other self-inflicted injuries in observational analyses.},
url = {http://linkinghub.elsevier.com/retrieve/pii/S0895435616301366 http://www.ncbi.nlm.nih.gov/pubmed/27237061 http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC5124536},
volume = 79,
year = 2016
}