Antidepressant Treatment and Suicidality: Biostatistical/Methodological Solutions

抗抑郁治疗和自杀：生物统计/方法学解决方案

• 批准号: 8246644
• 负责人: ROBERT D GIBBONS
• 金额: $ 75.89万
• 依托单位: UNIVERSITY OF CHICAGO
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-09-25 至 2012-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8246644
• 关键词: Antidepressant; Treatment; Suicidality; Biostatistical; Methodological

DESCRIPTION (provided by applicant): ABSTRACT The purpose of this proposal is to develop, test, and apply new statistical methodologies that can be used to identify low base rate drug adverse event (AE) interactions. These new methods will then be applied to a wide range of existing non- experimental datasets to examine the relationship between antidepressants and suicide attempts and completion. We have designed this research project as an integral collaboration between biostatisticians, research psychiatrists and clinicians, economists, and pharmacoepidemiologists, working with large ecological and medical records/claims electronic patient databases covering years where antidepressant use is varying dramatically. Three major specific aims are proposed: (a) the development of new statistical surveillance methods for detecting drug-AE interactions, (b) the development and application of analytic methods for ecological and population data, and (c) the development of and application of statistical methods for analysis of person-level data from large scale medical records/claims databases both in the U.S. and in Europe. The datasets that we have been granted access to include the FDA spontaneous reporting system (SRS/AERS/MedWatch), electronic medical record/claims databases in the U.S. (VA, and PHARMetrics), and similar data from the Netherlands (PHARMO). The work in this proposal will be carried out by a research consortium that will study national and international drug safety issues. The multidisciplinary group includes the areas of statistics (Drs. Gibbons, (PI), Brown (co-PI), Bhaumik, Hur, Marcus, and Rosenbaum), psychiatry from adult (Mann), and child (Brent) perspectives, health economics/econometrics (Heckman), and pharmacoepidemiology (Valuck). Collaboration with members of the VA (Cunningham), and PHARMO (Erkens, Herings) is an integral part of the proposal. PUBLIC HEALTH RELEVANCE: The enormous human cost of suicide makes research and prevention a national priority. Traditional approaches to drug safety have proved inadequate to address current public health issues. Providing statistical and methodological advances for the active surveillance of Drug-AE interactions, such as antidepressants and suicide, is a necessary first step in the establishment of a science-based health policy system, and is the primary goal of this proposal.

描述（由申请人提供）：摘要本提案的目的是开发、测试和应用新的统计方法，可用于识别低基础率药物 不良事件（AE）相互作用。然后，这些新方法将应用于广泛的现有非实验数据集，以检查抗抑郁药与自杀企图和完成之间的关系。我们将该研究项目设计为生物统计学家，研究精神病学家和临床医生，经济学家和药物流行病学家之间的整体合作，与大型生态和医疗记录/索赔电子患者数据库合作，这些数据库涵盖了抗抑郁药使用变化显着的年份。提出了三个主要的具体目标：（a）开发用于检测药物-AE相互作用的新的统计监测方法，（B）开发和应用生态和人群数据的分析方法，以及（c）开发和应用统计方法，分析来自美国和欧洲大规模医疗记录/索赔数据库的个人水平数据。我们获准访问的数据集包括FDA自发报告系统（SRS/AERS/MedWatch）、美国的电子病历/索赔数据库（VA和PHARMO）以及荷兰的类似数据（PHARMO）。本提案中的工作将由一个研究联合会进行，该联合会将研究国家和国际药物安全问题。多学科小组包括统计学领域（Gibbons博士（PI）、Brown博士（共同PI）、Bhaumik博士、Hur博士、Marcus博士和Rosenbaum博士）、成人精神病学（Mann）和儿童精神病学（布伦特）、卫生经济学/计量经济学（Heckman）和药物流行病学（Valuck）。与VA（坎宁安）和PHARMO（Erkens，Herings）成员的合作是该提案的一个组成部分。公共卫生相关性：自杀的巨大人类成本使研究和预防成为国家优先事项。事实证明，传统的药物安全方法不足以解决当前的公共卫生问题。为药物-AE相互作用（如抗抑郁药和自杀）的主动监测提供统计学和方法学进展，是建立以科学为基础的卫生政策体系的必要的第一步，也是本提案的主要目标。