Meta-analysis of diagnostic test studies using individual patient data and aggregate data
Meta-analysis of diagnostic test studies using individual patient data and aggregate data
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DOI：
10.1002/sim.3441
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发表时间：
2008-12-20
影响因子：
2
通讯作者：
Williamson, Paula R.
中科院分区：
文献类型：
--
作者：
Riley, Richard D.;Dodd, Susanna R.;Williamson, Paula R.
诊断测试研究的荟萃分析提供了关于特定测试准确性的循证结果，通常涉及从每个研究中综合汇总数据（AD），例如2 × 2诊断准确性表。双变量随机效应荟萃分析（BRMA）可以适当地综合这些表，并得出临床结果。例如跨研究的总结敏感性和特异性。然而，将这些结果转化为实践可能受到研究间异质性的限制，并且它们与研究中的一些“平均”患者有关。在本文中，我们描述了来自诊断研究的个体患者数据（IPD）的荟萃分析如何导致更适合个体患者的临床结果。我们开发了扩展BRMA框架的IPD模型，以包括研究水平的协变量，这有助于解释研究之间的异质性。还有患者水平的协变量，它允许人们评估患者特征油测试准确性的影响。我们表明，纳入患者水平的协变量需要仔细分离研究内和跨研究的准确性协变量效应，因为后者特别容易混淆。我们的模型通过模拟进行评估，并扩展到允许IPD研究与AD研究相结合，因为IPD并不总是适用于所有研究。应用于23项研究，评估耳温计诊断儿童发烧的准确性，其中16项为IPD， 7项为AD。模型显示，研究之间的异质性部分是由使用不同的测量设备来解释的。但没有证据表明，全是婴儿会影响诊断的准确性。版权所有(C) 2008约翰威利父子有限公司
A meta-analysis of diagnostic test Studies provides evidence-based results regarding the accuracy of a particular test, and usually involves synthesizing aggregate data (AD) from each study, such as the 2 by 2 tables of diagnostic accuracy. A bivariate random-effects meta-analysis (BRMA) can appropriately synthesize these tables, and leads to clinical results. Such as the summary sensitivity and specificity across studies. However, translating such results into practice may be limited by between-study heterogeneity and that they relate to some 'average' patient across studies.In this paper we describe how the meta-analysis of individual patient data (IPD) from diagnostic studies can lead to clinical results more tailored to the individual patient. We develop IPD models that extend the BRMA framework to include study-level covariates, which help explain the between-study heterogeneity. and also patient-level covariates, which allow one to assess the effect of patient characteristics oil test accuracy. We show how the inclusion of patient-level covariates requires a careful separation of within-study and across-study accuracy-covariate effects, as the latter are particularly prone to confounding. Our models are assessed through simulation and extended to allow IPD Studies to he combined with AD studies, as IPD are not always available for all Studies. Application is made to 23 studies assessing the accuracy of ear thermometers for diagnosing fever in children, with 16 IPD and 7 AD studies. The models reveal that between-study heterogeneity is partly explained by the use of different measurement devices. but there is no evidence that being all infant modifies diagnostic accuracy. Copyright (C) 2008 John Wiley & Sons, Ltd.