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

• 批准号: 8164771
• 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
• 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/8164771
• 关键词: Statistical; Methods; Software; Meta; analysis

DESCRIPTION (provided by applicant): 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 application 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 application, 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. PUBLIC HEALTH RELEVANCE: The overall goal of this project is to develop statistical methods and related software for meta-analysis of diagnostic tests. The proposed statistical methodology will be broadly applicable to the statistical analysis and interpretation of complex data sets arising in diagnostic test studies. It will improve comparative effectiveness research and public health by facilitating the diagnosis and treatment of cancer, cardiovascular, infectious and other diseases.

描述（由申请人提供）：摘要 - 比较有效性研究从根本上依赖于对临床结果的准确评估。评估工具的数量越来越多，以及成本的快速升级，在临床实践中对诊断测试的科学严格比较产生了越来越多的需求。与传统的荟萃分析应用相比，诊断测试的荟萃分析提出了许多其他统计挑战，例如对照临床试验的荟萃分析。特别是，诊断准确性不能通过一项措施充分总结；通常使用两种措施，最常见的敏感性和特异性，或者呈阳性和负有可能性比，两种相关。此外，诊断准确性参数可能取决于疾病的患病率。为了响应AHRQ PAR-10-168，该应用程序的总体目标是开发尖端的多元统计方法，并将其集成到公开可用的，易于使用的软件中，以增强比较诊断测试研究的荟萃分析的一致性，适用性和概括性。在此应用程序中，我们假设存在一个黄金标准。在诊断测试的荟萃分析中，黄金标准偏差不完美的问题是未来研究的主题。具体而言，我们将着重于开发统计方法和相关软件的：（1）当某些研究使用情况病例对照设计和某些研究使用队列设计时，对疾病患病率进行诊断测试的元分析，这在实践中很常见，但是从未解决过方法论上的影响； （2）纠正验证偏差，是由于金标准对诊断测试的荟萃分析进行诊断测试的荟萃分析，如果没有正确处理的数据和验证偏见不当处理，则可能会导致精确参数（包括敏感性和特异性）的准确性参数的偏见估计。我们建议通过实际数据应用和模拟对这些方法的优势和缺点进行经验评估。所提出的统计方法将广泛适用于比较诊断测试的元分析。它将通过促进各种癌症，心血管，传染性和其他疾病的诊断来改善公共卫生。这两个目标的完成将直接通过使用Winbugs和R统计语言在用户友好的软件中实施的最先进的方法来直接受益于AHRQ的比较有效性研究计划，这些方法将免费提供给公众。 公共卫生相关性：该项目的总体目标是开发用于诊断测试荟萃分析的统计方法和相关软件。所提出的统计方法将广泛适用于诊断测试研究中引起的复杂数据集的统计分析和解释。它将通过促进癌症，心血管，传染和其他疾病的诊断和治疗来改善比较有效性研究和公共卫生。