权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

Statistical disease modeling and clinimetrics to prepare for preventive trials in huntington disease

统计疾病模型和临床计量学，为亨廷顿病的预防性试验做准备

基本信息

批准号：
10213850
负责人：
Jane S Paulsen
金额：
$ 54.83万
依托单位：
UNIVERSITY OF WISCONSIN-MADISON
依托单位国家：
美国
项目类别：
财政年份：
2017
资助国家：
美国
起止时间：
2017-07-01 至 2023-03-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10213850
关键词：
Advisory Committees Age of Onset Algorithms Assessment tool Behavioral Biological Cell Death Clinic Clinical Trials Clinical Trials Design Cognitive Data Development Devices Diagnosis Discrimination Disease Disease Progression Disease model Documentation Drug Evaluation Enrollment Evaluation Evaluation Research Floor Functional disorder Future Gene Silencing Genes Genetic Goals Guidelines Healthcare Heterogeneity Huntington Disease Huntington gene Image Individual International Intervention Joints Label Medical Methods Modeling Motor Mutate Natural History Neurodegenerative Disorders Neurons Onset of illness Outcome Outcomes Research Participant Pathologic Patients Performance Pharmaceutical Economics Phenotype Positioning Attribute Preventive Preventive Clinical Trial Psychometrics Quality of life Radiologic Health Recommendation Reporting Research Research Subjects Sampling Secondary to Selection Criteria Severity of illness Societies Statistical Methods Statistical Models Testing Time United States Dept. of Health and Human Services United States Food and Drug Administration Validity and Reliability Work base clinical decision-making clinical outcome assessment cost design disorder subtype genetic testing interest mutant neuron loss novel predictive test prevent preventive intervention product development recruit social stigma success targeted treatment testing uptake tool volunteer

项目摘要

Project Summary Huntington disease (HD) is a fatal, costly, autosomal dominant neurodegenerative disease with no available disease-modifying treatments. While genetic testing can identify the presence of the mutant HTT gene, there are no markers to document the initiation of pathological changes or demarcate when preventive interventions are optimal to maximize quality of life. While clinical trials to slow progression and delay or prevent onset are beginning, methods to assess their efficacy are lacking. The proposed research will fill these gaps in our ability to design preventive clinical trials for HD. First, we will use the legacy PREDICT data to develop statistical models of onset, progression rate and phenotypic heterogeneity and then we will recruit 250 participants to complete the field's best Clinical Outcome Assessments (COAs) for premanifest HD and subject them to clinimetric tests of reliability, validity and responsiveness so future preventive trialists can utilize the information to design well-powered and efficient trials to delay the onset or slow the progression of HD

项目概要亨廷顿病 (HD) 是一种致命的、昂贵的、常染色体显性神经退行性疾病，目前尚无可用的治疗方法。疾病缓解治疗。虽然基因测试可以识别突变 HTT 基因的存在，但没有标记来记录病理变化的开始或在预防性干预时进行划分是最大限度提高生活质量的最佳选择。虽然减缓进展、延迟或预防发病的临床试验正在进行中首先，缺乏评估其功效的方法。拟议的研究将填补我们能力的这些空白设计 HD 的预防性临床试验。首先，我们将使用遗留的 PREDICT 数据来开发统计数据发病、进展率和表型异质性模型，然后我们将招募 250 名参与者完成该领域最佳的预定义 HD 临床结果评估 (COA) 并对其进行评估可靠性、有效性和响应性的临床测试，以便未来的预防性试验人员可以利用这些信息设计有力且高效的试验来延迟 HD 的发生或减缓 HD 的进展