Methods for Retrospective Multi-site Research

回顾性多地点研究方法

• 批准号: 8456050
• 负责人: MARK A ECKERT
• 金额: $ 29.21万
• 依托单位: MEDICAL UNIVERSITY OF SOUTH CAROLINA
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-05-01 至 2017-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8456050
• 关键词: Address; Affect; Archives; Attention deficit hyperactivity disorder; Autistic Disorder; Bayesian Method; Behavior; Behavior Disorders; Behavioral; Biological; Biological Markers; Brain region; Case-Control Studies; Classification; Clinical; Complex; Computer software; Computers; Consensus; Data; Data Analyses; Data Set; Databases; Development; Diagnosis; Disease; Dyslexia; Etiology; Exhibits; Face; Generations; Goals; Heterogeneity; Human; Hybrids; Image; Java; Label; MRI Scans; Measures; Methods; Modeling; Negative Finding; Neurobiology; Phase; Privacy; Procedures; Process; Published Comment; Quality Control; Reading Disabilities; Research; Research Design; Resources; Sample Size; Sampling; Scientist; Site; Software Tools; Source; Speed; Statistical Methods; Time; Treatment Efficacy; Vision; base; comparison group; data sharing; design; effective therapy; efficacy testing; endophenotype; expectation; method development; neurogenetics; neuroimaging; new technology; novel; programs; response; sound; treatment effect; usability

DESCRIPTION (provided by applicant): Methods for retrospective multi-site research will be developed in this project. Integrating data from multiple existing sources has the potential to substantially advance the study of behavior, particularly with respect to understanding complex behavioral disorders. Dyslexia is used as a model to develop methods for complex disorders because of the significant behavioral heterogeneity across people with dyslexia that could be used to develop a richer understanding of reading disability and other complex disorders with equally varied behavioral profiles such as autism or attention deficit hyperactivity disorder. Methods for three critical phases of retrospective multi-site research will be developed. Aim 1 is focused on subject privacy, including the development of an automated data de-identification software tool that can be used for multi-dimensional data sets. Aim 2 is focused on characterizing the behavioral heterogeneity within and across samples of complex disorders, [including the use of multiple imputation to address missing-ness in multi-site data sets.] Aim 3 is focused on how to appropriately analyze data from different samples that have included matched and unmatched case-control study designs. Our goal is to enhance the quality control and scientific power for behavioral and biologic studies of complex disorders, as well as advance the behavioral and neurobiological understanding of dyslexia. By developing standards for integrating behavioral and biological data, retrospective databases could be used to reveal etiologies and establish a consensus for the effective treatment of complex behavioral disorders.

描述（由申请人提供）：本项目将开发回顾性多地点研究方法。整合来自多个现有来源的数据有可能大大推进行为研究，特别是在理解复杂的行为障碍方面。阅读障碍被用作开发复杂疾病方法的模型，因为阅读障碍患者之间存在显着的行为异质性，可以用来更丰富地了解阅读障碍和其他具有同样不同行为特征的复杂疾病，例如自闭症或注意力缺陷多动障碍。将开发回顾性多地点研究的三个关键阶段的方法。目标1专注于主体隐私，包括开发可用于多维数据集的自动数据去识别软件工具。目标 2 的重点是表征复杂疾病样本内部和样本之间的行为异质性，[包括使用多重插补来解决多站点数据集中的缺失问题。]目标 3 的重点是如何正确分析来自不同样本的数据，这些样本包括匹配和不匹配的病例对照研究设计。我们的目标是增强复杂疾病的行为和生物学研究的质量控制和科学力量，并促进对阅读障碍的行为和神经生物学的理解。通过制定整合行为和生物学数据的标准，回顾性数据库可用于揭示病因并为有效治疗复杂行为障碍建立共识。