Quantifying the association between progression-free survival and overall survival in oncology trials using Kendall's tau.

Weber, Enya and Titman, Andrew Charles (2019) Quantifying the association between progression-free survival and overall survival in oncology trials using Kendall's tau. Statistics in Medicine, 38 (5). pp. 703-719. ISSN 0277-6715

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Abstract

This paper considers methods for estimating the association between progression-free and overall survival in oncology trials. Copula-based, non-parametric and illness-death model-based methods are reviewed. In addition, the approach based on an underlying illness-death model is generalized to allow general parametric models. The performance of these methods, in terms of bias and efficiency, is investigated through simulation and also illustrated using data from a clinical trial of treatments for colon cancer. The simulations suggest that the illness-death model-based method provides good estimates of Kendall's tau across several scenarios. In some situations copula-based methods perform well but their performance is sensitive to the choice of copula. The Clayton copula is most appropriate in scenarios which might realistically reflect an oncology trial, but the use of copula models in practice is questionable.

Item Type:
Journal Article
Journal or Publication Title:
Statistics in Medicine
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2600/2613
Subjects:
ID Code:
128136
Deposited By:
Deposited On:
12 Oct 2018 09:22
Refereed?:
Yes
Published?:
Published
Last Modified:
23 Sep 2020 03:50