Mediation analysis of time‐to‐event endpoints accounting for repeatedly measured mediators subject to time‐varying confounding

In this article, we will present statistical methods to assess to what extent the effect of a randomised treatment (versus control) on a time‐to‐event endpoint might be explained by the effect of treatment on a mediator of interest, a variable that is measured longitudinally at planned visits throug...

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Vydáno v:Statistics in medicine Ročník 38; číslo 24; s. 4828 - 4840
Hlavní autoři: Vansteelandt, Stijn, Linder, Martin, Vandenberghe, Sjouke, Steen, Johan, Madsen, Jesper
Médium: Journal Article
Jazyk:angličtina
Vydáno: England Wiley Subscription Services, Inc 30.10.2019
John Wiley and Sons Inc
Témata:
Cardiovascular Diseases - epidemiology
Cardiovascular Diseases - prevention & control
Confounding Factors, Epidemiologic
Diabetes Mellitus, Type 2 - drug therapy
Diabetic Angiopathies - epidemiology
Diabetic Angiopathies - prevention & control
Effect Modifier, Epidemiologic
Endpoint Determination
g‐formula
Humans
Hypoglycemic Agents - therapeutic use
Liraglutide - therapeutic use
longitudinal data
mediation
Models, Statistical
path‐specific effect
Randomized Controlled Trials as Topic
Research Design
time‐dependent confounding
path-specific effect
time-dependent confounding
mediation
g-formula
longitudinal data
ISSN:0277-6715, 1097-0258, 1097-0258
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Shrnutí:In this article, we will present statistical methods to assess to what extent the effect of a randomised treatment (versus control) on a time‐to‐event endpoint might be explained by the effect of treatment on a mediator of interest, a variable that is measured longitudinally at planned visits throughout the trial. In particular, we will show how to identify and infer the path‐specific effect of treatment on the event time via the repeatedly measured mediator levels. The considered proposal addresses complications due to patients dying before the mediator is assessed, due to the mediator being repeatedly measured, and due to posttreatment confounding of the effect of the mediator by other mediators. We illustrate the method by an application to data from the LEADER cardiovascular outcomes trial.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:0277-6715
1097-0258
1097-0258
DOI:10.1002/sim.8336