Jonker Marianne A, Vart Priya, Rodriguez Girondo Mar
Department for Health Evidence, Section Biostatistics, Radboud University Medical Center, Nijmegen, the Netherlands.
Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands.
Stat Methods Med Res. 2020 Aug;29(8):2344-2359. doi: 10.1177/0962280219893400. Epub 2019 Dec 27.
Information on the age at onset distribution of the asymptomatic stage of a disease can be of paramount importance in early detection and timely management of that disease. However, accurately estimating this distribution is challenging, because the asymptomatic stage is difficult to recognize for the patient and is often detected as an incidental finding or in case of recommended screening; the age at onset is often interval-censored. In this paper, we propose a method for the estimation of the age at onset distribution of the asymptomatic stage of a genetic disease based on ascertained pedigree data that take into account the way the data are ascertained to overcome selection bias. Simulation studies show that the estimates seem to be asymptotically unbiased. Our work is motivated by the analysis of data on facioscapulohumeral muscular dystrophy, a genetic muscle disorder. In our application, carriers of the genetic causal variant are identified through genetic screening of the relatives of symptomatic carriers and their disease status is determined by a medical examination. The estimates reveal an early age at onset of the asymptomatic stage of facioscapulohumeral muscular dystrophy.
有关疾病无症状阶段发病年龄分布的信息对于该疾病的早期检测和及时管理至关重要。然而,准确估计这种分布具有挑战性,因为无症状阶段对患者来说难以识别,且常常是作为偶然发现或在推荐筛查时被检测到;发病年龄通常是区间删失的。在本文中,我们基于已确定的系谱数据提出一种估计遗传疾病无症状阶段发病年龄分布的方法,该方法考虑了数据的确定方式以克服选择偏倚。模拟研究表明,估计值似乎是渐近无偏的。我们的工作是受对面肩肱型肌营养不良(一种遗传性肌肉疾病)数据的分析所推动。在我们的应用中,通过对有症状携带者的亲属进行基因筛查来识别遗传致病变异的携带者,并通过医学检查确定他们的疾病状态。估计结果显示面肩肱型肌营养不良无症状阶段的发病年龄较早。