On cross-odds ratio for multivariate competing risks data

Abstract

The cross-odds ratio is defined as the ratio of the conditional odds of the occurrence of one cause-specific event for one subject given the occurrence of the same or a different cause-specific event for another subject in the same cluster over the unconditional odds of occurrence of the cause-specific event. It is a measure of the association between the correlated cause-specific failure times within a cluster. The joint cumulative incidence function can be expressed as a function of the marginal cumulative incidence functions and the cross-odds ratio. Assuming that the marginal cumulative incidence functions follow a generalized semiparametric model, this paper studies the parametric regression modeling of the cross-odds ratio. A set of estimating equations are proposed for the unknown parameters and the asymptotic properties of the estimators are explored. Non-parametric estimation of the cross-odds ratio is also discussed. The proposed procedures are applied to the Danish twin data to model the associations between twins in their times to natural menopause and to investigate whether the association differs among monozygotic and dizygotic twins and how these associations have changed over time.

Fig. 1.

Estimated probability of both twins experiencing natural menopause (a) based on a constant cross odds-ratio for π_i,1|j,1(t,t) for MZ twins (solid line) and DZ twins (broken line), and under independence (dotted line). (b) Similar curves for the probability of joint occurrence of natural menopause and hormonal treatment in a twin pair based on constant cross odds-ratio for π_i,1|j,3(t,t) and under independence (solid line).