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

Research output: Contribution to journalJournal article

Published
<mark>Journal publication date</mark>28/02/2019
<mark>Journal</mark>Statistics in Medicine
Issue number5
Volume38
Number of pages17
Pages (from-to)703-719
Publication StatusPublished
Early online date12/10/18
<mark>Original language</mark>English

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.