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The population-attributable fraction for time-dependent exposures and competing risks - A discussion on estimands

Authors :
von Cube, Maja
Schumacher, Martin
Bailly, Sebastien
Timsit, Jean-Francois
Lepape, Alain
Savey, Anne
Machut, Anais
Wolkewitz, Martin
Source :
Stat Med, 2019; 38: 3880-3895
Publication Year :
2019

Abstract

The population-attributable fraction (PAF) quantifies the public health impact of a harmful exposure. Despite being a measure of significant importance an estimand accommodating complicated time-to-event data is not clearly defined. We discuss current estimands of the PAF used to quantify the public health impact of an internal time-dependent exposure for data subject to competing outcomes. To overcome some limitations, we proposed a novel estimand which is based on dynamic prediction by landmarking. In a profound simulation study, we discuss interpretation and performance of the various estimands and their estimators. The methods are applied to a large French database to estimate the health impact of ventilator-associated pneumonia for patients in intensive care.<br />Comment: A revision has been submitted

Details

Database :
arXiv
Journal :
Stat Med, 2019; 38: 3880-3895
Publication Type :
Report
Accession number :
edsarx.1904.08692
Document Type :
Working Paper
Full Text :
https://doi.org/10.1002/sim.8208