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Updated: Jan 23, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
The population-attributable fraction for time-dependent exposures and competing risks-A discussion on estimands
Maja von Cube1,2, Martin Schumacher1,2, Sébastien Bailly3,4
1Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany.
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 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.
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