INSERM, Bordeaux Population Health Research Center, Univ. Bordeaux, Bordeaux, France.
Section of Biostatistics, Department of Public Health, University of Copenhagen, Copenhagen, Denmark.
Stat Methods Med Res. 2020 Mar;29(3):752-764. doi: 10.1177/0962280219842271. Epub 2019 Apr 16.
Pseudo-values provide a method to perform regression analysis for complex quantities with right-censored data. A further complication, interval-censored data, appears when events such as dementia are studied in an epidemiological cohort. We propose an extension of the pseudo-value approach for interval-censored data based on a semi-parametric estimator computed using penalised likelihood and splines. This estimator takes interval-censoring and competing risks into account in an illness-death model. We apply the pseudo-value approach to three mean value parameters of interest in studies of dementia: the probability of staying alive and non-demented, the restricted mean survival time without dementia and the absolute risk of dementia. Simulation studies are conducted to examine properties of pseudo-values based on this semi-parametric estimator. The method is applied to the French cohort PAQUID, which included more than 3,000 non-demented subjects, followed for dementia for more than 25 years.
伪值为右删失数据的复杂量提供了回归分析的方法。当在流行病学队列中研究痴呆等事件时,就会出现间隔删失数据这种更复杂的情况。我们提出了一种基于使用惩罚似然和样条的半参数估计器的伪值方法的扩展,用于间隔删失数据。该估计器在疾病-死亡模型中考虑了间隔删失和竞争风险。我们将伪值方法应用于痴呆研究中三个感兴趣的均值参数:存活且无痴呆的概率、无痴呆的限制性平均生存时间和痴呆的绝对风险。进行了模拟研究以检验基于该半参数估计器的伪值的性质。该方法应用于包括 3000 多名无痴呆受试者且随访痴呆超过 25 年的法国队列 PAQUID。