Please use this identifier to cite or link to this item: http://hdl.handle.net/2381/38918
Title: Flexible parametric modelling of the cause-specific cumulative incidence function
Authors: Lambert, Paul C.
Wilkes, S. R.
Crowther, Michael J.
First Published: 22-Dec-2016
Publisher: Wiley
Citation: Statistics in Medicine, 2016
Abstract: Competing risks arise with time-to-event data when individuals are at risk of more than one type of event and the occurrence of one event precludes the occurrence of all other events. A useful measure with competing risks is the cause-specific cumulative incidence function (CIF), which gives the probability of experiencing a particular event as a function of follow-up time, accounting for the fact that some individuals may have a competing event. When modelling the cause-specific CIF, the most common model is a semi-parametric proportional subhazards model. In this paper we propose the use of flexible parametric survival models to directly model the cause-specific CIF where the effect of follow-up time is modelled using restricted cubic splines. The models provide smooth estimates of the cause-specific CIF with the important advantage that the approach is easily extended to model time-dependent effects. The models can be fitted using standard survival analysis tools by a combination of data expansion and introducing time-dependent weights. Various link functions are available that allow modelling on different scales and have proportional subhazards, proportional odds and relative absolute risks as particular cases. We conduct a simulation study to evaluate how well the spline functions approximate subhazard functions with complex shapes. The methods are illustrated using data from the European Blood and Marrow Transplantation Registry showing excellent agreement between parametric estimates of the cause-specific CIF and those obtained from a semi-parametric model. We also fit models relaxing the proportional subhazards assumption using alternative link functions and/or including time-dependent effects.
DOI Link: 10.1002/sim.7208
ISSN: 0277-6715
eISSN: 1097-0258
Links: http://onlinelibrary.wiley.com/doi/10.1002/sim.7208/full
http://hdl.handle.net/2381/38918
Embargo on file until: 22-Dec-2017
Version: Post-print
Status: Peer-reviewed
Type: Journal Article
Rights: Copyright © 2016, Wiley. Deposited with reference to the publisher’s open access archiving policy.
Description: The file associated with this record is under embargo until 12 months after publication, in accordance with the publisher's self-archiving policy. The full text may be available through the publisher links provided above.
Appears in Collections:Published Articles, Dept. of Health Sciences

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