Statistical Modelling 2 (2002), 89102
Genetic analysis of cause of death in a mixture model of bivariate
lifetime data
Andreas Wienke,
Max Planck Institute for Demographic Research,
Rostock
Germany
e-mail: wienke@demogr.mpg.de
Kaare Christensen & Axel Skytthe,
Danish Center for Demographic Research, and the Danish Twin Registry,
University of Southern Denmark
Odense
Denmark
Anatoli I. Yashin,
Max Planck Institute for Demographic Research,
Rostock
Germany
Abstract:
A mixture model in
multivariate survival analysis is presented, whereby heterogeneity among
subjects creates divergent paths for the individual's risk of experiencing an
event (i.e., disease), as well as for the associated length of survival.
Dependence among competing risks is included and rendered testable. This method
is an extension of the bivariate correlated gamma-frailty model. It is applied
to a data set on Danish twins, for whom cause-specific mortality is known. The
use of multivariate data solves the identifiability problem which is inherent
in the competing risk model of univariate lifetimes. We analyse the influence
of genetic and environmental factors on frailty. Using a sample of 1470
monozygotic (MZ) and 2730 dizygotic (DZ) female twin pairs, we apply five
genetic models to the associated mortality data, focusing particularly on death
from coronary heart disease (CHD). Using the best fitting model, the
inheritance risk of death from CHD was 0.39 (standard error 0.13). The results
from this model are compared with the results from earlier analysis that used
the restricted model, where the independence of competing risks was assumed.
Comparing both cases, it turns out, that heritability of frailty on mortality
due to CHD change substantially. Despite the inclusion of dependence, analysis
confirms the significant genetic component to an individual's risk of mortality
from CHD. Whether dependence or independence is assumed, the best model for
analysis with regard to CHD mortality risks is an AE model, implying that
additive factors are responsible for heritability in susceptibility to CHD. The
paper ends with a discussion of limitations and possible further extensions to
the model presented.
Keywords:
Coronary heart disease, Dependent competing risks, Frailty, Mixture models,
Survival analysis
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