The population-attributable fraction for time-dependent exposures and competing risks-A discussion on estimands.
Maja Katharina von CubeMartin SchumacherSébastien BaillyJean-François TimsitAlain LepapeAnne SaveyAnais MachutMartin WolkewitzPublished in: Statistics in medicine (2019)
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 that 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.
Keyphrases
- public health
- end stage renal disease
- electronic health record
- ejection fraction
- newly diagnosed
- healthcare
- chronic kidney disease
- global health
- big data
- peritoneal dialysis
- prognostic factors
- mental health
- air pollution
- intellectual disability
- human health
- risk assessment
- climate change
- adverse drug
- machine learning
- health information
- skeletal muscle
- patient reported outcomes
- adipose tissue
- acute respiratory distress syndrome
- patient reported
- extracorporeal membrane oxygenation