The population-attributable fraction for time-dependent exposures and competing risks - A discussion on estimands
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.
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Cite
@article{arxiv.1904.08692,
title = {The population-attributable fraction for time-dependent exposures and competing risks - A discussion on estimands},
author = {Maja von Cube and Martin Schumacher and Sebastien Bailly and Jean-Francois Timsit and Alain Lepape and Anne Savey and Anais Machut and Martin Wolkewitz},
journal= {arXiv preprint arXiv:1904.08692},
year = {2019}
}
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A revision has been submitted