A bivariate joint frailty model with mixture framework for survival analysis of recurrent events with dependent censoring and cure fraction
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McLachlan, Geoffrey J
Ng, Shu Kay
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Abstract
In the study of multiple failure time data with recurrent clinical endpoints, the classical independent censoring assumption in survival analysis can be violated when the evolution of the recurrent events is correlated with a censoring mechanism such as death. Moreover, in some situations, a cure fraction appears in the data because a tangible proportion of the study population benefits from treatment and becomes recurrence free and insusceptible to death related to the disease. A bivariate joint frailty mixture cure model is proposed to allow for dependent censoring and cure fraction in recurrent event data. The latency part of the model consists of two intensity functions for the hazard rates of recurrent events and death, wherein a bivariate frailty is introduced by means of the generalized linear mixed model methodology to adjust for dependent censoring. The model allows covariates and frailties in both the incidence and the latency parts and it further accounts for the possibility of cure after each recurrence. It includes the joint frailty model and other related models as special cases. An EM-type algorithm is developed to provide residual maximum likelihood estimation of model parameters. Through simulation studies, the performance of the model is investigated under different magnitudes of dependent censoring and cure rate. The model is applied to data sets from two colorectal cancer studies to illustrate its practical value.
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Biometrics
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76
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3
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DP170100907
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© 2020 John Wiley & Sons Ltd. This is the peer reviewed version of the following article: A bivariate joint frailty model with mixture framework for survival analysis of recurrent events with dependent censoring and cure fraction, Biometrics, 2020, 76 (3), pp. 753-766, which has been published in final form at https://doi.org/10.1111/biom.13202. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. This article may not be enhanced, enriched or otherwise transformed into a derivative work, without express permission from Wiley or by statutory rights under applicable legislation. Copyright notices must not be removed, obscured or modified. The article must be linked to Wiley’s version of record on Wiley Online Library and any embedding, framing or otherwise making available the article or pages thereof by third parties from platforms, services and websites other than Wiley Online Library must be prohibited.
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Subject
Applied statistics
Statistics
Other mathematical sciences
Biostatistics
EM algorithm
bivariate frailty
random effect
terminal event
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Tawiah, R; McLachlan, GJ; Ng, SK, A bivariate joint frailty model with mixture framework for survival analysis of recurrent events with dependent censoring and cure fraction, Biometrics, 2020, 76 (3), pp. 753-766