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Statistical Methods and Software for Meta-analysis of Diagnostic Tests

诊断测试荟萃分析的统计方法和软件

基本信息

批准号：
8267547
负责人：
Haitao Chu
金额：
$ 4.99万
依托单位：
UNIVERSITY OF MINNESOTA
依托单位国家：
美国
项目类别：
财政年份：
2011
资助国家：
美国
起止时间：
2011-07-01 至 2013-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8267547
关键词：
Statistical Methods Software Meta analysis

项目摘要

Statistical Methods and Software for Meta-analysis of Diagnostic Tests Principal Investigator: Haitao Chu, M.D., Ph.D. Summary Comparative effectiveness research relies fundamentally on accurate assessment of clinical outcomes. The growing number of assessment instruments, as well as the rapid escalation in the cost has generated the increasing need for scientifically rigorous comparisons of the diagnostic tests in clinical practice. Meta-analysis of diagnostic tests presents many additional statistical challenges compared to traditional meta-analysis applications such as meta-analysis of controlled clinical trials. In particular, diagnostic accuracy cannot be adequately summarized by one measure; two measures are typically used, most often sensitivity and specificity, or alternatively positive and negative likelihood ratios, and either two are correlated. Furthermore, diagnostic accuracy parameters may depend on disease prevalence. In response to AHRQ PAR-10-168, the overall goal of this proposal is to develop cutting-edge multivariate statistical methods, and to integrate them into publicly available, easy-to-use software to enhance the consistency, applicability, and generalizability of the meta-analysis of comparative diagnostic test studies. In this proposal, we assume that a gold standard exists; the problem of imperfect gold standard bias in a meta-analysis of diagnostic tests is a topic for future research. Specifically, we will focus on developing statistical methods and related software for: (1) Meta- analysis of diagnostic tests accounting for disease prevalence when some studies use case-control design and some studies use cohort design, which is common in practice but methodological ramifications have never been addressed; (2) Correcting verification bias from meta-analysis of diagnostic tests due to biased sampling of whom is being tested by the gold standard, which can lead to biased estimation of accuracy parameters including sensitivities and specificities if the missing data and verification bias are not appropriately handled. We propose to perform empirical assessment of the strengths and weaknesses of these methods through real data applications and simulations. The proposed statistical methodology will be broadly applicable to the meta- analysis comparing diagnostic tests. It will improve public health by facilitating the diagnosis of various cancers, cardiovascular, infectious and other diseases. Completion of these two aims will directly benefit the comparative effectiveness research program at AHRQ by providing state-of-the art methods implemented in user-friendly software using WinBUGS and R statistical languages that will be made freely available to the public.

诊断试验Meta分析的统计方法和软件主要研究者：Haitao Chu，M.D.，博士总结比较有效性研究从根本上依赖于对临床结果的准确评估。评估工具的数量不断增加，以及费用的迅速上升，在临床实践中对诊断测试的科学严格比较的需求日益增加。荟萃分析与传统的荟萃分析相比，应用程序，如对照临床试验的荟萃分析。特别是，诊断准确性不能被通过一个指标充分总结;通常使用两个指标，最常见的是敏感性和特异性，或者备选地阳性和阴性似然比，并且两者中的任一个是相关的。此外，委员会认为，诊断准确性参数可以取决于疾病流行率。根据AHRQ PAR-10-168，该提案的总体目标是开发最先进的多元统计方法，并将其整合转化为公开可用的，易于使用的软件，以提高一致性，适用性和普遍性，比较诊断试验研究的荟萃分析。在这个建议中，我们假设金本位制存在;诊断测试荟萃分析中的不完美金标准偏倚问题是未来的一个主题 research.具体而言，我们将重点开发统计方法和相关软件，用于：（1）Meta- 当一些研究使用病例对照设计时，分析诊断测试解释疾病患病率，一些研究使用队列设计，这在实践中很常见，但方法学上的分歧从未（2）纠正由于有偏抽样导致的诊断测试荟萃分析的验证偏倚的人正在接受金标准的测试，这可能导致准确度参数的有偏估计包括敏感性和特异性，如果缺失数据和核查偏差没有得到适当处理。我们建议通过真实的方法对这些方法的优点和缺点进行实证评估。数据应用和模拟。拟议的统计方法将广泛适用于Meta 分析比较诊断测试。它将通过促进各种疾病的诊断来改善公共卫生。癌症、心血管疾病、传染病和其他疾病。这两个目标的实现，将直接有利于 AHRQ的比较有效性研究计划，提供最先进的方法，使用WinBUGS和R统计语言的用户友好型软件，将免费提供给公众