Cross Design Synthesis: Combining Evidence About Antidepressants and Suicidality

交叉设计综合：结合抗抑郁药和自杀的证据

基本信息

批准号：
8036718
负责人：
Kelly J Kelleher
金额：
$ 26.55万
依托单位：
RESEARCH INST NATIONWIDE CHILDREN'S HOSP
依托单位国家：
美国
项目类别：
财政年份：
2010
资助国家：
美国
起止时间：
2010-03-01 至 2012-02-29
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8036718
关键词：
Address Adverse effects Affect Antidepressive Agents Anus Behavior Benefits and Risks Caring Characteristics Clinical Trials Cohort Studies Communities Complement Computer software Consensus Data Data Sources Decision Making Development Diagnosis Disease Effectiveness Elderly Empirical Research Enrollment Ensure Exclusion Criteria Feeling suicidal Funding General Population Goals Growth Healthcare Heterogeneity Incidence Individual Intervention Investigation Knowledge Light Link Longevity Major Depressive Disorder Mental Depression Mental disorders Meta-Analysis Methodology Methods Modeling National Institute of Mental Health New Agents Observational Study Outcome Patients Persons Pharmaceutical Preparations Play Policies Population Population Heterogeneity Practice based research Principal Investigator Protocols documentation Provider Psychiatry Psychotherapy Randomized Controlled Trials Research Research Design Research Personnel Risk Role Science Scientific Evaluation Selective Serotonin Reuptake Inhibitor Services Societies Solutions Source Staging Statistical Methods Suicide Surface Therapeutic United States Food and Drug Administration Variant Work Youth accomplished suicide base clinical care community setting design evidence base improved interdisciplinary collaboration interest meetings method development middle age patient population programs randomized trial research study response routine practice success tool user-friendly young adult

项目摘要

DESCRIPTION (provided by applicant): Every scientific investigation takes place in the context of uncertain evidence about a question of interest. We believe that the primary goal of research synthesis is to bring differing opinions concerning such questions to consensus. The focus of our application is the question regarding the evidence for an association between antidepressant use and suicidality and builds on our reanalysis of the FDA meta-analysis of antidepressant use and suicidality in youth (Kaizar, Greenhouse, Kelleher, Seltman 2005). Our work is motivated by the recognition that the existing evidence base that can inform this question is available from both experimental and non-experimental studies, and is neither perfect, in the sense that experiments may be rigorous but restricted, and non-experimental studies more general but may be biased nor complete, in the sense that the available outcomes of interest may be indirect (e.g., suicidal ideation/behavior and not completed suicide). The primary work of this application is the conduct of a research synthesis to help advance our understanding of the relationship among antidepressant use, suicide, and suicidality. Specifically, we will use cross-design synthesis, a relatively new research strategy for combining data from studies with complementary designs, to evaluate and combine evidence from both randomized trials and non-experimental studies. Our primary synthesis will include randomized trials of antidepressants both with and without psychotherapy along with data from at least two larger studies that include antidepressant use. We are particularly concerned with the development and application of methods that will facilitate the combining of evidence from multiple data sources, including methods for adjusting studies for factors that affect their external validity, and methods for exploring the effects of biases that affect internal validity. Our approach will be based on the use of Bayesian hierarchical models. We focus on Bayesian hierarchical models as one solution to the problem of making inferences when syntheses require not only modeling of within and between study heterogeneity, but also the qualitative differences of study types. The Bayesian approach will also help facilitate sensitivity analyses for assessing the robustness of inferences to various model inputs. We will also develop accessible and user friendly statistical software programs to implement the methodology that we develop.

描述（由申请人提供）：每项科学研究都是在有关感兴趣问题的证据不确定的背景下进行的。我们认为，研究综合的首要目标是使有关此类问题的不同意见达成共识。我们申请的重点是关于抗抑郁药使用与自杀之间关联的证据问题，并建立在我们对 FDA 对青少年抗抑郁药使用和自杀的荟萃分析进行重新分析的基础上（Kaizar、Greenhouse、Kelleher、Seltman 2005）。我们工作的动机是认识到现有的证据基础可以从实验和非实验研究中获得，并且既不完美，也不是完美的，因为实验可能是严格但有限的，而非实验研究更多是一般性的，但可能是有偏见的或不完整的，因为感兴趣的可用结果可能是间接的（例如，自杀意念/行为和未完成的自杀）。该应用程序的主要工作是进行研究综合，以帮助加深我们对抗抑郁药使用、自杀和自杀倾向之间关系的理解。具体来说，我们将使用交叉设计综合（一种相对较新的研究策略，将研究数据与互补设计相结合）来评估和结合随机试验和非实验研究的证据。我们的初步综合将包括有或没有心理治疗的抗抑郁药的随机试验，以及至少两项包括抗抑郁药使用的大型研究的数据。我们特别关注有助于整合来自多个数据源的证据的方法的开发和应用，包括调整影响外部效度因素的研究的方法，以及探索影响内部效度的偏差影响的方法。我们的方法将基于贝叶斯分层模型的使用。当综合不仅需要对研究内部和之间的异质性进行建模，而且还需要对研究类型的定性差异进行建模时，我们将重点放在贝叶斯分层模型上，作为推理问题的一种解决方案。贝叶斯方法还将有助于促进敏感性分析，以评估各种模型输入的推论的稳健性。我们还将开发易于使用且用户友好的统计软件程序来实施我们开发的方法。