Modernizing Meta-Analysis to Facilitate Comparative Effectiveness Reviews

现代化荟萃分析以促进比较有效性审查

基本信息

批准号：
8582588
负责人：
CHRISTOPHER H. SCHMID
金额：
$ 23.65万
依托单位：
BROWN UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2009
资助国家：
美国
起止时间：
2009-09-30 至 2013-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8582588
关键词：
Modernizing Meta Analysis Facilitate Comparative

项目摘要

DESCRIPTION (provided by applicant): The growing number of treatment choices, as well as the rapid escalation in the cost of health care has spawned the need for scientifically rigorous comparisons of the efficacy and safety of drugs, devices and treatments in clinical practice. Most quantitative comparisons carried out by the Evidence Based Practice Centers (EPCs) funded by AHRQ have relied on meta-analyses comparing two treatments for one outcome. But many of the questions posed to assessors involve multiple treatments and multiple outcomes. Standard assessments have approached these questions separately, leading to a plethora of analyses to interpret and no quantitatively rigorous methods for integrating them. Multivariate statistical methods offer a solution. Statistical methods for simultaneously analyzing multiple treatments or for analyzing multiple outcomes have appeared in the past decade, along with applications to important problems. Because they are new, these methods have not penetrated into the standard clinical research arsenal and remain the provenance of experts. To make them more practical, particularly for groups like EPCs, we propose further development of the methods, empirical assessment of their strengths and weaknesses, integration into publicly available, easy to-use software and application to key clinical questions. In particular, we propose a three-year project to carry out the following three Specific Aims focusing on intervention studies: 1) Develop new and enhance existing techniques for the statistical analysis of possibly incomplete multivariate meta-analytic data involving multiple (> 2) treatments, multiple outcomes or categories of outcomes and multiple follow-up times; 2) Implement these methods in an ongoing open-source software project so users will have access to customized and customizable algorithms and support for their use through analytic wizards that will guide users to appropriate statistical methods and presentation quality graphics and reports; and 3) Apply multivariate methods to a set of key clinical questions that we have identified as well as to topics in the EPC program as they arise over the course of this application so as to gain empirical insight into their strengths and weaknesses and to demonstrate their contribution to improving comparative effectiveness reviews. Completion of these three aims will directly benefit the comparative effectiveness research program at AHRQ by providing state-of-the art methods implemented in user-friendly open-source software that will be made freely available to the public. The open-source nature of the software will enable it to incorporate all of the capabilities of the R and OpenBugs statistical programs and will facilitate the incorporation of new methods as they are developed. The user interface will allow the non-statistically expert user access to these features without the need for programming expertise.

描述（由申请人提供）：治疗选择的数量越来越多，以及医疗保健成本的迅速升级，催生了对临床实践中药物，设备和治疗方法的科学严格比较。由AHRQ资助的基于证据的实践中心（EPC）进行的大多数定量比较依赖于比较两种治疗方法的荟萃分析。但是，提出的许多问题涉及多种治疗和多种结果。标准评估已分别解决了这些问题，导致大量分析以解释，并且没有定量严格的整合方法。多元统计方法提供了解决方案。在过去的十年中，出现了用于同时分析多种治疗或分析多种结果的统计方法，以及对重要问题的应用。因为它们是新的，所以这些方法尚未渗透到标准的临床研究中，并且仍然是专家的出处。为了使它们更加实用，尤其是对于像EPC这样的团体，我们建议进一步发展这些方法，对其优势和劣势的经验评估，融入公共可用的，易于使用的软件以及对关键临床问题的应用。特别是，我们提出了一个为期三年的项目，以执行以下三个针对干预研究的特定目标： 1）开发新的和增强现有技术，以涉及多种（> 2）治疗，多种结果或类别的结果和多个随访时间的多元治疗，多种（> 2）处理的多变量荟萃分析数据的统计分析； 2）在正在进行的开源软件项目中实现这些方法，以便用户可以访问自定义和可自定义的算法，并通过分析向导进行使用，以指导用户使用适当的统计方法和演示质量图形和报告；和 3）将多元方法应用于我们已经确定的一系列关键临床问题以及EPC计划中的主题，因为它们在本应用过程中出现，以便获得对其优势和劣势的经验见解，并证明他们在提高比较有效性评论方面的贡献。这三个目标的完成将直接受益于比较有效性研究计划 AHRQ通过提供用户友好的开源软件实施的最先进的方法，该方法将自由地向公众提供。该软件的开源性质将使IT能够结合R和OpenBugs统计程序的所有功能，并将促进在开发新方法时纳入新方法。用户界面将允许非统计的专家用户访问这些功能，而无需编程专业知识。