Modeling the cumulative incidence function of multivariate competing risks data allowing for within-cluster dependence of risk and timing

Abstract

We propose to model the cause-specific cumulative incidence function of multivariate competing risks data using a random effects model that allows for within-cluster dependence of both risk and timing. The model contains parameters that makes it possible to assess how the two are connected, e.g. if high-risk is related to early onset. Under the proposed model, the cumulative incidences of all failure causes are modeled and all cause-specific and cross-cause associations specified. Consequently, left-truncation and right-censoring are easily dealt with. The proposed model is assessed using simulation studies and applied in analysis of Danish register-based family data on breast cancer.

Citation

@article{cederkvistmcif,
    author = {Cederkvist, Luise and Holst, Klaus K and Andersen, Klaus K and Scheike, Thomas H},
    title = {Modeling the cumulative incidence function of multivariate competing risks data allowing for within-cluster dependence of risk and timing},
    journal = {Biostatistics},
    volume = {20},
    number = {2},
    pages = {199-217},
    year = {2018},
    month = {01},
    issn = {1465-4644},
    doi = {10.1093/biostatistics/kxx072},
}