Characterizing Factors that Impact the Evolution of Neurocysticercosis Cysts: A Cyst-Level Analysis Using New Statistical Methods for Complex Longitudinal Data

项目总结 尽管越来越多的证据表明脑囊虫病(NC)囊肿的进化在大脑内有所不同，但生命过程 对包囊寄生虫的研究相对较少。我们了解到，囊性病变的演变与 脑实质和脑实质外的位置，可能根据患者的年龄和性别，但对此知之甚少 在整个进化阶段或根据囊性和患者特征的转变的时间，也不是如何 阿苯达唑(ALB)等驱虫药的疗效受囊肿性和患者特征的影响。我们的 大多数研究只检查患者水平的集合，这一事实阻碍了对囊性病变演变的理解 脑内NC囊性负荷的测量。然而，同一患者中的单个NC囊肿可以演变为 不同的是，白蛋白可能会杀死一些寄生虫，但对同一患者中的其他寄生虫几乎没有影响；只有通过 通过对单个囊性病变的追踪，我们可以了解这些差异。因此，在这个项目中，我们的目标是分解 患者级别的数据到囊肿级，并使用多状态建模来检查单个囊肿经 从疾病进展的角度来看，进化的各个阶段。尽管多态模型可以处理多变量 对于纵向数据，我们的NC包囊数据带来了额外的挑战：(1)由于预审查，数据是间隔删失的 指定的数据收集时间表，(2)由于后续丢失，数据可以被信息性的权利审查， 这导致丢失的数据可能不是随机的，(3)数据被左审查，因为患者输入 对先前存在的囊肿和感染时间的研究尚不清楚，以及(4)因为多个囊肿可能在 同样的患者，甚至在相同的大脑位置，我们有多个水平的相关数据。在这项研究中，我们 提出了一种嵌套脆弱性的选择模型嵌入时齐马尔可夫多状态联合模型 NC包囊数据。在推理方面，我们将考虑基于最大似然的方法。使用这些新功能 方法：我们建议进行囊性水平分析，以确定影响囊性和患者特征的因素。 应用2001-05年的随机对照试验数据研究非霍奇金淋巴瘤囊性病变和白蛋白治疗效果 在厄瓜多尔进行了一项为期24个月的跟踪调查，对178名患者进行了白蛋白治疗和安慰剂治疗的比较 在基线、1、6、12和24个月进行脑成像(CT/MRI)。这一方法论方法将 通过提供更详细的关于囊虫进化过程的信息和 影响白蛋白对本课程影响的因素。这些分析的结果将增加我们对 在改变ALB有效性的因素中，朝着更精确的患者发展的第一步 治疗方案，从而改善了患者的预后。拟议的统计方法还可能具有 应用于通过预定义的临床状态演变并影响多个身体的其他疾病的建模 在采用间歇性数据收集和各种形式的审查的纵向研究中对这些地区进行评估。

PROJECT SUMMARY Despite accumulating evidence that neurocysticercosis (NC) cyst evolution varies within the brain, the life course of the encysted parasite remains relatively understudied. We understand that cyst evolution differs between parenchymal and extraparenchymal brain locations and possibly by patient age and sex, but little is known about the timing of the transitions through the stages of evolution overall or by cyst and patient characteristics, nor how cyst and patient characteristics impact the effect of anthelminthic treatment such as albendazole (ALB). Our understanding of cyst evolution is hindered by the fact that most studies examine only patient-level aggregate measures of NC cyst burden within the brain. However, individual NC cysts in the same patient can evolve differently, and ALB may kill some parasites but have little effect on others within the same patient; only by following individual cysts can we understand these differences. Therefore, in this project, we aim to disaggregate patient-level data to the cyst-level and use multistate modeling to examine transitions of individual cysts through stages of evolution from the disease progress perspective. Although multistate models can handle multivariate longitudinal data, our NC cysts data pose additional challenges: (1) the data are interval-censored due to pre- specified data collection schedules, (2) the data can be informatively right-censored due to loss to follow-up, which results in missing data that may not be random, (3) the data is left-censored because patients enter a study with pre-existing cysts and the time of infection is unknown, and (4) because multiple cysts can be within the same patient, and even within the same brain location, we have multilevel correlated data. In this study, we propose a selection-model embedded time-homogeneous Markov multistate joint model with nested frailty for the NC cyst data. Inference wise, we will consider the maximum likelihood-based approach. Using these new methods, we propose to conduct cyst-level analysis to identify the cyst and patient characteristics that impact NC cyst evolution and ALB treatment effectiveness using data from a 2001-05 randomized controlled trial conducted in Ecuador that compared ALB treatment to placebo among 178 patients over 24 months follow-up with brain imaging (CT/MRI) conducted at baseline, months 1, 6, 12 and 24. This methodological approach will advance neurocysticercosis research by providing more detailed information on the cyst evolutionary course and factors that modify the impact of ALB on this course. Results from these analyses will increase our understanding of the factors that modify the effectiveness of ALB, first step towards the development of more precise patient treatment options and thereby improved patient outcomes. The proposed statistical methods may also have applications to modeling other diseases that evolve through predefined clinical states and impact multiple body regions when assessed in longitudinal studies with intermittent data collection and various forms of censoring.