ANALYTICAL METHODS FOR OBSERVATIONAL DRUG USER COHORTS

描述：(申请人摘要) NIDA和其他机构最近资助了许多纵向 对非法吸毒者健康/行为的观察性队列研究 已经提供了无价的信息。然而，新的分析方法 为此，需要观察性队列数据来回答重要问题 关于(I)吸毒者目前/变化的发病率和死亡模式 以及(Ii)干预措施的使用、成本和收益。作为观察性的 直到最近，队列数据才大量存在，方法 对这类数据的分析还不够完善。该项目提出了 开发必要的统计/流行病学方法以进一步分析 现有的观察性药物使用者队列数据。一个全面的 统计/流行病学小组将开发和应用方法学 药物使用研究专家的支持。十项大型研究将在 对他们的数据进行建模和应用。四个主要领域 与纵向观察相关的统计/流行病学研究 将开发药物使用者数据：(1)竞争对手的描述和分析 构成药物使用相关疾病自然病史的事件和 发病率(即艾滋病、结核病、肝炎、服药过量、心内膜炎、 等)；(2)对流行病学偏差进行调整，以便对艾滋病毒进行比较 吸毒者与其他危险人群的疾病进展和估计 对疾病进展的治疗作用；(3)非参数模型 更准确地描述复杂的关系(线性、生存和 其他)发生在观察性吸毒者数据中；(4)重复分析 与重复用药有关的事件，如费用、持续时间和时间 病情(即住院、性传播疾病、复发 成瘾)。 该项目将开发流行病学/统计工具，以分析 非法药物使用者数据，并记录这些方法以供将来使用(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 解决与流行性感冒流行病学有关的关键医学和科学问题 吸毒者中的HIV-1和其他疾病。

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.