Use and development of statistical mediation techniques to understand the survival gap between males and females with cystic fibrosis

囊性纤维化是一种限制生命的遗传性疾病，全世界有超过70,000人受到影响。它是由囊性纤维化跨膜调节蛋白基因突变引起的，该基因为囊性纤维化跨膜电导调节蛋白提供指令，该蛋白起着氯离子和碳酸氢根离子跨细胞膜运输通道的作用。这种运输障碍导致覆盖在细胞上的粘液变厚和脱水，这些粘液既干扰了正常的功能，又容易被病原体定植，导致体内许多器官系统的进行性损害，包括胰腺、肺、肾脏和消化系统，最终导致寿命缩短。目前的治疗方法主要是减轻CF造成的损害，因为目前还没有治疗方法可以治愈CF。对于2019年出生的英国婴儿，男性的中位生存期预计为51.6年，女性为45.7年。近几十年来，尽管生存时间增加了，但男性和女性之间的这种生存差距出现在有记录的数据中，在其他国家也观察到了这种差距。到目前为止，对于这种生存差距还没有明确的解释，这为这个项目提供了动力。性行为似乎很可能在生命过程中对疾病发展的几个方面产生影响，进而影响生存。先前的研究表明：患有CFT的女性首次获得多种病原体的年龄比男性更早，感染特定病原体的女性比男性死亡率更高，40岁后女性预测的FEV%(与相同年龄、性别、身高和种族的无CFF的人相比，用力呼气量的比例)比男性下降得更大，而且，在CFTR基因严重携带者中，女性囊性纤维化相关糖尿病的患病率更高。该研究的假设是，性别影响疾病发展的这些方面和其他方面共同导致了存活率的差异。该项目将使用英国囊性纤维化登记处的纵向数据，该登记处成立于1995年。这是一个由囊性纤维化信托管理的中央数据库。在英国，超过99%的CF患者同意将他们的数据提交到数据库。该数据库是一个大型数据集，不仅包含来自13,000多人的记录和来自年度患者审查的140,000多条记录，而且还包括记录的宽度和复杂性，以及在每次年度审查中收集的250多个变量的数据。该项目将使用截至2018年的数据。该项目的目标之一是通过总结关键变量中的性别差异，了解哪些变量显示了性别差异。然而，该项目的主要目的是通过中介分析，了解性别对生存的影响如何通过中间变量发挥作用，从而进一步理解导致这种生存差距的因果路径。被考虑的调解人将有不同的类型：绝对的、连续的和事件发生的时间，所有的都被重复测量。最近在调解分析的统计方法方面有了相当大的发展，其中有多个调解人，而且结果是事件发生的时间，这个项目提供了一个使用和开发这些技术的令人兴奋的机会。该项目将使我在以下方面获得技能：-处理和分析来自大型观察性患者登记的纵向数据-将最新的统计调解分析和其他因果推理方法应用于实质性研究问题-开发统计方法和使用模拟研究的方法评估-与临床顾问和数据专家联系以改进研究问题

Cystic Fibrosis (CF) is a life limiting genetic disorder affecting over 70,000 people worldwide. It is caused by a mutation in the Cystic Fibrosis Transmembrane Regulator (CFTR) gene which supplies the instructions for the cystic fibrosis transmembrane conductance regulator protein which acts as a channel to transport chloride and bicarbonate ions across cell membranes. This impaired transport results in thickened and dehydrated mucus covering the cells that both interferes with normal functioning and is prone to colonisation by pathogens causing progressive damage in many organ systems of the body including the pancreas, lungs, kidneys and digestive system, and ultimately leads to a reduced life-span.Current treatments concentrate on mitigating the damage caused by CF since currently there are no treatments that can cure CF. For babies born in 2019 in the UK, median survival is predicted to be 51.6 years for males and 45.7 years for females. This survival gap between males and females has been present in recorded data over recent decades even as survival times have increased and it has also been observed in other countries. There is as yet no clear explanation for this survival gap and it provides the motivation for this project. It seems likely that sex impacts on several aspects of disease progression through the life course, which in turn affects survival. Previous research has shown that: females with CF first acquire many pathogens at an earlier age than males, females infected with particular pathogens have increased mortality compared to men, after the age of 40 females have greater decline in FEV% predicted (the proportion of Forced Expiratory Volume compared to a person without CF of the same age, sex, height and ethnicity) than males and also that, of those with severe CFTR genotypes, females have higher prevalence of cystic fibrosis related diabetes. The hypothesis is that these and other aspects of disease progression affected by sex are, in combination, responsible for the survival disparity.The project will use longitudinal data from the UK Cystic Fibrosis Registry which was set up in 1995. It is a centralised database managed by the Cystic Fibrosis Trust. Over 99% of people with CF in the UK have consented to their data being submitted to the database. The database is a large data set not only in containing records from over 13,000 people and over 140,000 records from annual patient reviews but also in terms of the width and complexity of the records with data collected on over 250 variables at each annual review. The project will use data up to 2018.One aim of the project is to understand which variables show divergence between the sexes by summarising sex differences in key variables. The main aim of the project, however, is to understand how the effect of sex on survival may act through intermediate variables by using mediation analysis and so further the understanding of the causal pathways leading to this survival disparity. The mediators considered will be of different types: categorical, continuous and time-to-event, and all are repeatedly measured. There has been considerable recent development in statistical methodology for mediation analysis where there are multiple mediators and also where the outcome is time-to-event and this project presents an exciting opportunity to use and develop these techniques.The project will allow me to gain skills in: - Handling and analysing longitudinal data from a large observational patient registry - Applying state of the art statistical mediation analysis and other causal inference methodology to a substantive research question - Developing statistical methodology and assessment of methods using simulation studies - Liaising with clinical advisors and data experts to refine the research questions