Statistical Methods and Software for Meta-analysis of Diagnostic Tests

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。由于评估工具的数量不断增加，以及费用的迅速上升，越来越需要在临床实践中对诊断测试进行科学严格的比较。与传统的荟萃分析应用（如对照临床试验的荟萃分析）相比，诊断测试的荟萃分析提出了许多额外的统计挑战。特别是，诊断的准确性不能充分概括为一个措施；通常使用两种测量方法，最常见的是灵敏度和特异性，或者是正似然比和负似然比，两者都是相关的。此外，诊断准确性参数可能取决于疾病的流行程度。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、适用性和推广性。在这个应用程序中，我们假设存在一个金本位；诊断测试的荟萃分析中不完美的金标准偏差问题是未来研究的主题。具体来说，我们将专注于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，对诊断测试进行Meta分析，这在实践中很常见，但方法上的分歧从未得到解决；(2)纠正诊断试验元分析中因金标准测试对象抽样偏倚而导致的验证偏差，如果数据缺失和验证偏差处理不当，可能导致灵敏度和特异性等准确性参数的估计偏倚。我们建议通过实际数据应用和模拟对这些方法的优缺点进行实证评估。提出的统计方法将广泛适用于比较诊断试验的元分析。它将促进各种癌症、心血管疾病、传染病和其他疾病的诊断，从而改善公众健康。这两个目标的完成将通过提供使用WinBUGS和R统计语言的用户友好软件实现的最先进的方法，直接使AHRQ的比较有效性研究项目受益，这些软件将免费提供给公众。

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.