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)：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。随着评估仪器数量的增加以及成本的迅速上升，在临床实践中越来越需要对诊断测试进行科学严格的比较。与传统的荟萃分析应用相比，诊断试验的荟萃分析提出了许多额外的统计学挑战，如对照临床试验的荟萃分析。特别是，诊断准确性不能用一种衡量标准来充分概括；通常使用两种衡量标准，最常见的是敏感性和特异性，或者是阳性和阴性似然比，其中任何一种都是相关的。此外，诊断准确性参数可能取决于疾病流行率。为了响应AHRQ PAR-10-168，本应用程序的总体目标是开发尖端的多变量统计方法，并将它们集成到公开可用的、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、适用性和普适性。在这一应用中，我们假设存在黄金标准；诊断测试的荟萃分析中的不完美黄金标准偏差问题是未来研究的主题。具体地说，我们将专注于为以下方面开发统计方法和相关软件：(1)当一些研究使用病例对照设计和一些研究使用队列设计时，对考虑疾病患病率的诊断测试进行荟萃分析，这在实践中很常见，但方法学分支从未得到解决；(2)通过诊断测试的荟萃分析纠正验证偏差，这是由于黄金标准对谁进行了有偏见的抽样，如果没有适当处理缺失数据和验证偏差，这可能会导致对准确性参数的偏差估计，包括灵敏度和特异度。我们建议通过实际数据应用和模拟来对这些方法的优势和劣势进行实证评估。所提出的统计方法将广泛适用于Meta分析比较诊断检验。它将通过促进对各种癌症、心血管疾病、传染病和其他疾病的诊断来改善公共健康。这两个目标的完成将直接惠及AHRQ的比较有效性研究方案，因为它提供了使用WinBUGS和R统计语言的用户友好软件中实施的最先进的方法，这些方法将免费向公众提供。 公共卫生相关性：该项目的总体目标是开发用于诊断测试的荟萃分析的统计方法和相关软件。拟议的统计方法将广泛适用于诊断测试研究中出现的复杂数据集的统计分析和解释。它将促进癌症、心血管疾病、传染病和其他疾病的诊断和治疗，从而提高比较有效性研究和公共卫生。