Etiology and Modeling Core

病因学和建模核心

基本信息

批准号：
8425167
负责人：
Gary Douglas Slade
金额：
$ 20.16万
依托单位：
UNIV OF NORTH CAROLINA CHAPEL HILL
依托单位国家：
美国
项目类别：
财政年份：
2004
资助国家：
美国
起止时间：
2004-09-30 至
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/8425167
关键词：
Address Advisory Committees Affect Agreement Biological Blood specimen Caring Classification Clinical Cluster Analysis Complex Consult Consultations Data Data Analyses Data Collection Detection Development Diagnosis Environmental Exposure Epidemiologic Methods Equation Etiology Fatigue Genetic Genetic Markers Individual Joints Label Leukocytes Manuals Measures Meta-Analysis Methods Modeling Molecular Molecular Profiling Odds Ratio Pain Pain Measurement Pain-Free Pathway interactions Patients Persistent pain Phenotype Physiological Plasma Principal Component Analysis Procedures Process Proteins Protocols documentation Research Personnel Resources Risk Risk Factors Sample Size Specific qualifier value Structural Models Subgroup Symptoms System Transcript Variant abstracting clinical research site data management genetic association genetic profiling meetings novel programs protein profiling psychologic psychological distress trait

项目摘要

Abstract: Complex Persistent Pain Conditions: Etiology and Modeling Core. This core will support four functions relevant to subprojects and cores of this program: 1) convene an Internal Scientific Advisory Committee (ISAC) to insure consistency of data collection and analysis strategies for the program's five complex persistent pain conditions (CPPCs); 2) implement consistent study protocols and data collecfion procedures throughout the program; 3) undertake statistical analysis of pooled data from all five of the program's CPPCs; 4) consultation with project Pis in their analysis of aims specific to single CPPCs. During the first year, the ISAC will be devoted to overseeing development of study protocols and data collecfion methods. In subsequent years the ISAC will devote greater effort to refining the program's hypothesized causal model and specifying the data analysis strategy. Data collection procedures will be made consistent through creation of program-wide data management systems. Analysis of pooled data from all five of the program's CPPCs will address the program's specific aims that focus on genetic, physiologic, psychological and environmental exposures contribufing to the risk of one or more CPPCs. Conventional epidemiological methods for analysis of casecontrol studies will be compare odds of exposure between 1,500 CPPC cases and 1,230 controls who have none of the CPPCs. This sample size will allow us to identify risk factors that affect as few as 5% of subjects and that have exposure odds ratios as low as 1.6, while controlling for multiple tesfing (eg. from among 3,000 genetic markers) with an appropriate rate of false discovery. The most promising risk factors identified through these convenfional methods Will be evaluated jointly in multivariate structural equation models that isolate individual effect, interactions and pathways among causes. Investigators in the etiology and modeling care will consult with project Pis in their analysis of specific CPPCs which will follow a similar strategy of odds ratio estimation and detection of interacfion, followed by multivariate causal modeling. For these analyses, 300 cases with a specific CPPC will be contrasted with at least 1,230 controls.

抽象的：复杂的持续疼痛条件：病因和建模核心。该核心将支持与该计划的子项目和核心相关的四个功能：1）召集内部科学咨询委员会（ISAC），以确保该计划的五个复杂持续性疼痛条件（CPPC）的数据收集和分析策略的一致性； 2）在整个过程中实施一致的研究方案和数据集合程序程序; 3）对该计划的CPPC的所有五个数据进行统计分析； 4）与Project PIS进行咨询，以分析针对单个CPPC的目标。在第一年，ISAC将致力于监督研究方案和数据collection方法的开发。在随后的几年中分析策略。通过创建程序范围的数据管理系统，将使数据收集过程保持一致。对该计划的所有CPPC的汇总数据的分析将解决该计划的具体目的，该目标的重点是遗传，生理，心理和环境暴露，从而有助于一个或多个CPPC的风险。用于分析Casecontol的常规流行病学方法研究将是比较1,500例CPPC病例和1,230例CPPC对照之间暴露的几率。该样本量将使我们能够识别影响少于5％的受试者的风险因素，并且暴露赔率比低至1.6，同时控制多个TESFING（例如，从3,000个遗传标记中）具有适当的错误发现率。通过这些便利的方法将在隔离原因之间的个体效果，相互作用和途径的多元结构方程模型中共同评估。病因和建模护理研究人员将在对特定CPPC的分析中咨询PIS PIS，该分析将遵循类似的估计和检测策略的策略，然后进行多元因果建模。对于这些分析，300 具有特定CPPC的病例将与至少1,230个对照对比。