TY - JOUR

T1 - Estimating twin concordance for bivariate competing risks twin data

AU - Scheike, Thomas Harder

AU - Holst, Klaus Kähler

AU - von Bornemann Hjelmborg, Jacob

PY - 2014/3

Y1 - 2014/3

N2 - For twin time-to-event data, we consider different concordance probabilities, such as the casewise concordance that are routinely computed as a measure of the lifetime dependence/correlation for specific diseases. The concordance probability here is the probability that both twins have experienced the event of interest. Under the assumption that both twins are censored at the same time, we show how to estimate this probability in the presence of right censoring, and as a consequence, we can then estimate the casewise twin concordance. In addition, we can model the magnitude of within pair dependence over time, and covariates may be further influential on the marginal risk and dependence structure. We establish the estimators large sample properties and suggest various tests, for example, for inferring familial influence. The method is demonstrated and motivated by specific twin data on cancer events with the competing risk death. We thus aim to quantify the degree of dependence through the casewise concordance function and show a significant genetic component

AB - For twin time-to-event data, we consider different concordance probabilities, such as the casewise concordance that are routinely computed as a measure of the lifetime dependence/correlation for specific diseases. The concordance probability here is the probability that both twins have experienced the event of interest. Under the assumption that both twins are censored at the same time, we show how to estimate this probability in the presence of right censoring, and as a consequence, we can then estimate the casewise twin concordance. In addition, we can model the magnitude of within pair dependence over time, and covariates may be further influential on the marginal risk and dependence structure. We establish the estimators large sample properties and suggest various tests, for example, for inferring familial influence. The method is demonstrated and motivated by specific twin data on cancer events with the competing risk death. We thus aim to quantify the degree of dependence through the casewise concordance function and show a significant genetic component

KW - casewise concordance

KW - concordance function

KW - cumulative incidence probability

KW - multivariate competing risks

KW - twins

KW - casewise concordance

KW - concordance function

KW - cumulative incidence probability

KW - multivariate competing risks

KW - twins

U2 - 10.1002/sim.6016

DO - 10.1002/sim.6016

M3 - Journal article

C2 - 24132877

VL - 33

SP - 1193

EP - 1204

JO - Statistics in Medicine

JF - Statistics in Medicine

SN - 0277-6715

IS - 7

ER -