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-猫眼课题宝

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

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

项目状态：

已结题

起止时间：

2017-07-01 至 2023-03-31

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

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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

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