Section of Biostatistics, University of Copenhagen, Øster Farimagsgade 5B, DK-1014 Copenhagen K, Denmark and Unit of Statistics & Pharmacoepidemiology, Danish Cancer Society Research Center, Strandboulevarden 49, DK-2100 Copenhagen Ø, Denmark.
Section of Biostatistics, University of Copenhagen, Øster Farimagsgade 5B, DK-1014 Copenhagen K, Denmark.
Biostatistics. 2019 Apr 1;20(2):199-217. doi: 10.1093/biostatistics/kxx072.
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.
我们建议使用随机效应模型来对多变量竞争风险数据的特定原因累积发生率函数进行建模，该模型允许风险和时间的聚类内相关性。该模型包含使评估两者之间关系成为可能的参数，例如，如果高风险与早期发病有关。在提出的模型下，对所有失败原因的累积发生率进行建模，并指定所有特定原因和交叉原因的关联。因此，很容易处理左截断和右删失。该模型使用模拟研究进行评估，并应用于分析丹麦基于登记的乳腺癌家族数据。
