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

影响神经囊尾蚴病包囊进化的特征因素：使用新的统计方法对复杂纵向数据进行包囊水平分析

• 批准号: 9978521
• 负责人: ELIZABETH A KELVIN
• 金额: $ 15.21万
• 依托单位: GRADUATE SCHOOL OF PUBLIC HEALTH AND HEALTH POLICY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-04-01 至 2023-09-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9978521
• 关键词: Address; Age; Albendazole; Anthelmintics; Body Regions; Brain; Brain imaging; Central Nervous System Infections; Characteristics; Clinical; Complex; Cyst; Data; Data Collection; Development; Disease; Ecuador; Effectiveness; Epidemiology; Event; Evolution; Gender; Health; Human; Image; Individual; Infection; Joints; Lead; Left; Life Cycle Stages; Location; Longitudinal Studies; Low income; Magnetic Resonance Imaging; Measures; Methodology; Methods; Modeling; Neurocysticercosis; Parasites; Patient-Focused Outcomes; Patients; Phase; Placebos; Precision therapeutics; Prednisone; Probability; Property; Randomized; Randomized Clinical Trials; Randomized Controlled Trials; Recording of previous events; Research; Resolution; Sampling; Schedule; Seizures; Specific qualifier value; Statistical Methods; Taenia solium; Techniques; Time; Treatment Effectiveness; Treatment outcome; United States; Use Effectiveness; base; burden of illness; calcification; clinical trial participant; data modeling; exhaustion; flexibility; follow-up; frailty; improved; improved outcome; nervous system disorder; sex; simulation; treatment effect

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.

项目摘要 尽管积累了证据表明神经囊肿（NC）囊肿的演化在大脑中有所不同，但生命过程 寄生虫的环境寄生虫仍然相对研究。我们了解囊肿的演化在 实质和脑外脑外脑位置，可能是患者年龄和性别，但对 通过总体或囊肿和患者特征的进化阶段过渡的时机，也不是如何 囊肿和患者特征会影响驱虫治疗（例如阿替唑（ALB））的影响。我们的 大多数研究仅检查患者级骨料的事实阻碍了对囊肿进化的理解 大脑内NC囊肿负担的度量。但是，同一患者中的单个NC囊肿可以进化 不同的是，ALB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。仅由 遵循单个囊肿，我们可以理解这些差异。因此，在这个项目中，我们旨在分类 患者级数据到囊肿级，并使用多层建模来检查单个囊肿的过渡 从疾病进步的角度来看，进化的阶段。尽管多层模型可以处理多变量 纵向数据，我们的NC囊肿数据提出了额外的挑战：（1）由于预性而进行间隔审查数据 指定的数据收集时间表，（2）由于随访的损失，数据可以进行右键验证， 这导致丢失的数据可能不是随机的，（3）由于患者输入A 先前存在的囊肿和感染时间的研究未知，（4），因为多个囊肿可以在 同一患者，甚至在同一大脑位置，我们都有多级相关数据。在这项研究中，我们 提出一个选择模型的嵌入式时间均匀的马尔可夫多态联合模型，具有嵌套脆弱的 NC囊肿数据。明智的推论，我们将考虑基于最大似然的方法。使用这些新 方法，我们建议进行囊肿级分析，以确定影响的囊肿和患者特征 NC囊肿演化和ALB治疗有效性，使用2001 - 05年随机对照试验的数据 在厄瓜多尔进行了24个月后178名患者的ALB治疗与安慰剂进行了比较 随着在基线1、6、12和24月进行的大脑成像（CT/MRI）。这种方法学方法将 通过提供有关囊肿进化过程和 改变ABS对本课程的影响的因素。这些分析的结果将增加我们的理解 改变了ALB有效性的因素，迈向更精确的患者的第一步 治疗选择，从而改善了患者的预后。提出的统计方法也可能具有 应用于建模其他疾病，这些疾病通过预定义的临床状态进化并影响多个身体 区域在纵向研究中进行间歇性数据收集和各种形式的检查时进行评估。