Cederkvist Luise, Holst Klaus K, Andersen Klaus K, Glidden David V, Frederiksen Kirsten, Kjaer Susanne K, Scheike Thomas H
Section of Biostatistics, University of Copenhagen, Øster Farimagsgade 5, POB 2099, Copenhagen K, DK-1014, Denmark.
Unit of Statistics, Bioinformatics and Registry, Danish Cancer Society Research Center, Strandboulevarden 49, Copenhagen Ø, DK-2100, Denmark.
Stat Med. 2017 May 10;36(10):1599-1618. doi: 10.1002/sim.7229. Epub 2017 Jan 23.
Familial aggregation and the role of genetic and environmental factors can be investigated through family studies analysed using the liability-threshold model. The liability-threshold model ignores the timing of events including the age of disease onset and right censoring, which can lead to estimates that are difficult to interpret and are potentially biased. We incorporate the time aspect into the liability-threshold model for case-control-family data following the same approach that has been applied in the twin setting. Thus, the data are considered as arising from a competing risks setting and inverse probability of censoring weights are used to adjust for right censoring. In the case-control-family setting, recognising the existence of competing events is highly relevant to the sampling of control probands. Because of the presence of multiple family members who may be censored at different ages, the estimation of inverse probability of censoring weights is not as straightforward as in the twin setting but requires consideration. We propose to employ a composite likelihood conditioning on proband status that markedly simplifies adjustment for right censoring. We assess the proposed approach using simulation studies and apply it in the analysis of two Danish register-based case-control-family studies: one on cancer diagnosed in childhood and adolescence, and one on early-onset breast cancer. Copyright © 2017 John Wiley & Sons, Ltd.
家族聚集性以及遗传和环境因素的作用可以通过使用易感性阈值模型进行分析的家族研究来探究。易感性阈值模型忽略了事件发生的时间，包括疾病发病年龄和右删失，这可能导致难以解释且可能有偏差的估计。我们按照在双胞胎研究中应用的相同方法，将时间因素纳入病例对照家系数据的易感性阈值模型中。因此，数据被视为来自竞争风险设定，并使用删失权重的逆概率来调整右删失。在病例对照家系设定中，认识到竞争事件的存在与对照先证者的抽样高度相关。由于存在多个可能在不同年龄被删失的家庭成员，删失权重逆概率的估计不像在双胞胎研究中那么直接，而是需要考虑。我们建议采用基于先证者状态的复合似然法，这显著简化了对右删失的调整。我们通过模拟研究评估所提出的方法，并将其应用于两项基于丹麦登记处的病例对照家系研究分析中：一项是关于儿童期和青少年期诊断的癌症，另一项是关于早发性乳腺癌。版权所有© 2017约翰威立父子有限公司。
