Estimating twin concordance for bivariate competing risks twin data

Thomas Harder Scheike, Klaus Kähler Holst, Jacob von Bornemann Hjelmborg

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

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
Original languageEnglish
JournalStatistics in Medicine
Volume33
Issue number7
Pages (from-to)1193-1204
ISSN0277-6715
DOIs
Publication statusPublished - 30. Mar 2014

Keywords

  • Breast Neoplasms/genetics
  • Cohort Studies
  • Computer Simulation
  • Denmark/epidemiology
  • Diseases in Twins/epidemiology
  • Female
  • Humans
  • Models, Statistical
  • Probability
  • Risk
  • Twins, Dizygotic/genetics
  • Twins, Monozygotic/genetics

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