ANALYTICAL METHODS FOR OBSERVATIONAL DRUG USER COHORTS

观察吸毒者群体的分析方法

• 批准号: 2331185
• 负责人: Mei Cheng Wang
• 金额: $ 44.95万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 1997
• 资助国家: 美国
• 起止时间: 1997-07-01 至 2000-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/2331185
• 关键词: HIV infections; clinical research; comorbidity; computer program /software; disease /disorder proneness /risk; drug abuse; epidemiology; health care cost /financing; health care service utilization; human immunodeficiency virus 1; human morbidity; human mortality; human subject; longitudinal human study; method development; model design /development; pathologic process; relapse /recurrence; statistics /biometry

DESCRIPTION: (Applicant's Abstract) NIDA and other agencies have recently funded numerous longitudinal observational cohort studies of health/behavior in illicit drug users that have already provided invaluable information. However, new analytic methods for this observational cohort data are needed to answer important questions about (i) the current/changing patterns of morbidity and death in drug users and (ii) the usage, costs, and benefits of interventions. As observational cohort data have not existed in large amounts until recently, methods of analysis for such data are not well developed. This project proposes to develop needed statistical/epidemiological methods to further analyze existing observational drug user cohort data. A comprehensive statistical/epidemiological team will develop and apply methodology with support from drug use study experts. Ten large studies will collaborate in modeling and applications towards their data. Four major areas of statistical/epidemiological research relevant to longitudinal observational drug user data will be developed: (1) Description and analysis of competing events that constitute the natural history of drug use related disease and morbidity (i.e., AIDS, tuberculosis, hepatitis, overdoses, endocarditis, etc.); (2) Adjustment for epidemiological biases to allow comparison of HIV disease progression in drug users versus other risk groups and estimation of treatment effects on this disease progression; (3) Nonparametric models to more accurately describe complicated relationships (linear, survival and other) occurring in observational drug user data; (4) Analysis of repeated events such as costs, duration and timing of repeating drug related conditions (i.e., hospitalizations, sexually transmitted diseases, relapses to addiction). This project will develop epidemiological/statistical tools to analyze illicit drug user data and document these methods for future use (i.e., with software). It will perform simultaneous comparative analysis of research questions in many observational drug cohort datasets. These analyses will resolve key medical and scientific issues concerning the epidemiology of HIV-1 and other diseases in drug users.

描述：（申请人的摘要） NIDA和其他机构最近资助了许多纵向 在非法吸毒者中对健康/行为的观察队列研究 已经提供了宝贵的信息。 但是，新的分析方法 对于此观察性队列数据，需要回答重要问题 关于（i）吸毒者的发病率和死亡的当前/变化模式 （ii）干预措施的使用，成本和收益。 作为观察 队列数据直到最近才大量存在， 此类数据的分析尚未得到很好的发展。 这个项目提议 开发所需的统计/流行病学方法来进一步分析 现有的观察药物用户队列数据。 全面 统计/流行病学团队将开发和应用方法论 药物使用研究专家的支持。 十项大型研究将合作 对其数据进行建模和应用。 四个主要领域 统计/流行病学研究与纵向观察有关 将开发药物用户数据：（1）竞争的描述和分析 构成与毒品使用相关疾病的自然历史的事件和 发病率（即艾滋病，结核病，肝炎，过量，心内膜炎， ETC。）; （2）调整流行病学偏见以允许艾滋病毒的比较 吸毒者与其他风险群体的疾病进展以及 治疗对这种疾病进展的影响； （3）非参数模型 更准确地描述复杂的关系（线性，生存和 其他）发生在观察药物用户数据中； （4）重复分析 诸如成本，持续时间和与重复药物相关的时间安排等事件 疾病（即住院，性传播疾病，复发 上瘾）。 该项目将开发流行病学/统计工具来分析 非法药物用户数据并记录以后使用的这些方法（即 软件）。 它将同时进行研究的比较分析 许多观察性药物队列数据集中的问题。 这些分析将 解决有关流行病学的关键医学和科学问题 吸毒者中的HIV-1和其他疾病。