无金标准情况下三个诊断试验评价方法

目的探讨三个诊断试验在无金标准情况下诊断试验方法及检出率、灵敏度、特异度的估计。方法根据Bayesian参数估计原理,利用Gibbs抽样方法得到后验密度估计。结果可计算出后验参数估值及其95?yesian可信区间。结论文中提出的方法可有效地估计无金标准情况下三个诊断试验的后验参数。     

无金标准诊断试验灵敏度和特异度的贝叶斯估计方法

目的 探讨在无金标准情况下诊断试验灵敏度和特异度的贝叶斯估计方法,并通过模拟实验验证此方法的有效性和适用性.方法 应用贝叶斯原理,结合一个或者两个对照诊断试验,采用对照诊断试验与待测诊断试验诊断结果相互独立或者存在相关模型;和两个对照诊断试验诊断结果存在相关,并且同时与待测诊断试验结果相互独立模型;以及一个对照诊断试验与待测诊断试验诊断结果存在相关,并且同时与另一个对照诊断试验诊断结果相互独立模型,对一种新的诊断方法的灵敏度、特异度进行估计.结果 模拟试验表明在先验信息相对准确的条件下,所给出的几种不同模型均能较准确的估计待测诊断方法的灵敏度和特异度,估测参数范围包括设定真值,并且估测参数均值基本与真实情况相同;此外,模拟实验结果表明,利用两个对照诊断试验模型估计参数的估计效果优于使用一个对照诊断试验模型时的参数估计效果.结论 本文介绍的贝叶斯方法能够有效地应用于无金标准诊断试验的评价,从而解决了无金标准诊断试验无法评价的难题.     

无金标准试验评价方法及其在唐氏综合征筛查中的应用

目的 介绍在无金标准情况下估计筛查试验参数的方法,评价唐氏综合征筛查试验.方法 采用Gibbs抽样方法构造markov链,估计唐氏综合征筛查试验的参数.结果 采用MCMC方法中的Gibbs抽样方法,估计出了利用母体血清AFP与游离betaHcg结合母体年龄别危险度在国内人群中筛查唐氏综合征试验的ROC曲线,从而得了试验的灵敏度、特异度和合适的阈值.结论 MCMC方法中的Gibbs抽样方法能够在缺少金标准的前提下,结合参数的先验分布较好地估计筛查试验的参数.     

无金标准条件下诊断试验评价贝叶斯相关模型构建及应用

目的探讨无金标准条件下诊断试验贝叶斯相关模型构建方法及应用条件。方法通过分析具有潜在真值的无金标准诊断试验评价模型,构建两个试验相关条件下的似然函数;利用共轭分布原理,构建灵敏度、特异度、患病率的先验分布;使用WinBUGS软件计算后验参数。通过234602名无偿献血员抗-HIV检测结果说明贝叶斯相关模型的应用。结果构建了无金标准时两次ELISA法检测抗-HIV的贝叶斯相关模型,发现两次ELISA的灵敏度相关系数为0.30,特异度相关系数为0.74;两次试验的联合灵敏度较单个试剂增高(P<0.05),特异度较单个试剂降低(P<0.05),但特异度降低的幅度明显小于灵敏度增高的幅度。结论应用贝叶斯相关模型可合理评价无金标准时联合试验的灵敏度和特异度。     

潜在分类模型在无金标准诊断试验中的评价

目的探讨无金标准诊断试验下灵敏度与特异度的估计方法。方法以三个诊断试验为例,利用潜在分类模型估计无金标准诊断试验的灵敏度、特异度及其95%可信区间。并将潜在分类模型估计的结果与Bayesian方法估计结果进行比较。结果三个诊断试验的灵敏度与特异度的95%可信区间均存在一定的重叠,表明两种方法估计结果较为相似。结论诊断试验的灵敏度与特异度在无金标准时是无法直接计算的,可利用潜在分类模型与Bayesian方法估算诊断试验的灵敏度与特异度。     

不同方差比双正态ROC参数估计样本量确定方法准确性探讨

目的 探讨不同方差比双正态参数估计时样本量确定方法的准确性,对最常用样本量估计方法--双正态法所估计样本量的准确性进行评价与修正.方法 采用Monte Carlo模拟试验,分别利用参数法和非参数法计算获得曲线下面积的参数估计值,获得实际所需样本量,对Obuchowski和Mcclish给出的不同方差比双正态ROC参数估计所需样本量的准确性进行评价,依据试验数据采用曲线拟合方法给出修正公式.结果 Obuchowski和Mcclish给出的方法是假定患病组诊断变量XA和非患病组诊断变量XN服从正态分布,样本量计算公式是以ROC曲线下面积估计值服从正态分布为前提导出的,但事实上随ROC曲线实际面积θ逐渐增大,样本估计量偏离正态,导致样本量估计结果不够准确,与实际样本需要量有一定差距.在其他条件相同的情况下,患病组与非患病组诊断变量方差比越大实际所需样本量越多,在患病组与非患病组诊断变量方差比分别为2∶1及3∶1的情况下,用Obuchowski和Mcclish方法计算出的样本量与实际所需样本量相差不是很大.根据Monte Carlo模拟试验的结果,给出了Obuchowski和Mcclish方法计算样本量的修正公式,该修正公式可有效地应用于实际.结论 Obuchowski和Mcclish方法计算的样本量进行ROC参数估计时需要调整,采用Monte Carlo方法估计的样本量,可以有效地进行双正态ROC参数估计,达到诊断试验评价要求.     

无金标准条件下含协变量的ROC曲线估计方法

目的阐明无金标准条件下,考虑协变量后估计ROC曲线的两部贝叶斯模型。方法介绍两部贝叶斯模型,结合实例,筛选无金标准条件下ROC曲线的影响因素,考虑协变量影响后,估计ROC曲线。结果两部贝叶斯模型不仅可探讨协变量对疾病状态的影响,而且可探讨协变量对诊断试验结果的影响,同时可计算不同协变量取值条件下ROC曲线下面积。结论两部贝叶斯模型可有效地解决无金标准条件下,考虑协变量影响的ROC曲线估计问题。     

基于潜分类方法评价无金标准条件下诊断试验的准确性

[目的]探讨无金标准条件下诊断试验准确性评价的潜分类方法。[方法]介绍潜分类模型在无金标准诊断试验评价中的原理、试验设计和评价方法,用两人群两试验实例说明潜分类方法的应用。[结果]对于二分类反应变量,假设条件独立和试验准确性稳定,至少需要两个人群两种试验方法或一个人群三种试验方法才能满足模型可识别性并用于频率学派统计评价;贝叶斯统计不需满足模型的可识别性,但需引入先验分布,且存在先验依赖性。[结论]潜分类方法可用于无金标准时的诊断试验评价,但要选择适合的试验设计和评价方法。     

ROC曲线下面积的ML估计与假设检验

目的 探讨诊断试验中配对设计资料的ROC分析方法。方法 在双正态模型基础下应用ML估计方法计算ROC曲线下面积，正态近似法估计面积的可信区间及假设检验。结果 由迭代法进行参数估计，得到ROC曲线下的面积、面积的标准误及置信区间，可计算出面积比较的U检验统计量。结论 可用于配对设计的诊断试验的比较和评价，包括对连续性和等级分类资料的处理。     

检查Cox模型比例风险假定的几种图示法

目的 检查Ｃｏｘ模型比例风险假定图示法的应用与比较。方法 介绍了基于Ｃｏｘ模型与ｋａｐｌｑｎ－ｍｅｉｅｒ法生存估计比较、Ｃｏｘ模型累积风险函数、ｓｃｈｏｅｎｆｅｌｄ残差和ｓｃｏｒｅ残差的图示法。结果 上述几种图示法均可不同程度地检查ＰＨ假定。结论 建议使用ｓｃｈｏｅｎｆｅｌｄ残差图和ｓｃｏｒｅ残差图，除评价ＰＨ假定外，前者可提供ＬＨＲＦ的非参数估计，后者可用于诊断观测对Ｃｏｘ模型参数估计的杠杆。     

Allergic bronchopulmonary aspergillosis in Italian cystic fibrosis patients: Prevalence and percentage of positive tests in the employed diagnostic criteria

The prevalence of allergic bronchopulmonary aspergillosis (ABPA) in cystic fibrosis (CF) patients is difficult to determine because the data in the literature are not homogeneous or comparable. ABPA and CF have similar clinical symptoms which make diagnosis difficult and underestimate the real dimensions of the problem. We conducted an epidemiological study on 3089 Italian CF patients to determine the prevalence of ABPA in Italy and verify the percentage of positive tests in the employed diagnostic criteria. Our results indicate that the prevalence of ABPA in Italian CF patients is 6.18%, mainly in adolescents and young adults. ABPA is diagnosed using clinical symptoms (presence of episodic bronchial obstructions or typical radiographic features) and on the basis of other criteria which can only be partially fulfilled in paediatric patients. Among the diagnostic tests the most sensitive are the total IgE (84.5%), specific IgE anti-Aspergillus fumigatus (81.6%) and the prick test (68.3%). In the absence of clinical symptoms and gold standard diagnostic tests, serological positivity and/or the skin test are not sufficient evidence to confirm the presence of ABPA.     

Combining multiple continuous tests for the diagnosis of kidney impairment in the absence of a gold standard

Receiver operating characteristic (ROC) curves are commonly used to summarize the classification accuracy of diagnostic tests. It is not uncommon in medical practice that multiple diagnostic tests are routinely performed or multiple disease markers are available for the same individuals. When the true disease status is verified by a gold standard (GS) test, a variety of methods have been proposed to combine such potential correlated tests to increase the accuracy of disease diagnosis. In this article, we propose a method of combining multiple diagnostic tests in the absence of a GS. We assume that the test values and their classification accuracies are dependent on covariates. Simulation studies are performed to examine the performance of the combination method. The proposed method is applied to data from a population-based aging study to compare the accuracy of three screening tests for kidney function and to estimate the prevalence of moderate kidney impairment.     

Evaluating medical diagnostic tests at the subunit level in the presence of verification bias

We advocate that medical diagnostic tests should be evaluated at the subunit level instead of the patient level if a disease can occur in multiple parts/units within a patient, for example, vessels, segments, ears, eyes etc. When a non-invasive test is compared to an invasive gold standard test, often not all of the subunits receive the gold standard test and verification bias is present if the subunits without the gold standard test are discarded. Here we address estimation and inference issues in assessing the performance of medical diagnostic tests at the subunit level while accounting for verification bias and the correlation among subunits. We present a weighted least squares approach and demonstrate how the method can be implemented by using the procedure PROC CATMOD from the popular SAS software. A cardiology example is presented and we discuss application of the method to the case of multiple tests and a single gold standard test.     

Modeling continuous diagnostic test data using approximate Dirichlet process distributions

There is now a large literature on the analysis of diagnostic test data. In the absence of a gold standard test, latent class analysis is most often used to estimate the prevalence of the condition of interest and the properties of the diagnostic tests. When test results are measured on a continuous scale, both parametric and nonparametric models have been proposed. Parametric methods such as the commonly used bi-normal model may not fit the data well; nonparametric methods developed to date have been relatively complex to apply in practice, and their properties have not been carefully evaluated in the diagnostic testing context. In this paper, we propose a simple yet flexible Bayesian nonparametric model which approximates a Dirichlet process for continuous data. We compare results from the nonparametric model with those from the bi-normal model via simulations, investigating both how much is lost in using a nonparametric model when the bi-normal model is correct and how much can be gained in using a nonparametric model when normality does not hold. We also carefully investigate the trade-offs that occur between flexibility and identifiability of the model as different Dirichlet process prior distributions are used. Motivated by an application to tuberculosis clustering, we extend our nonparametric model to accommodate two additional dichotomous tests and proceed to analyze these data using both the continuous test alone as well as all three tests together.     

Meta-analysis of diagnostic tests with imperfect reference standards.

We present a method to estimate the summary receiver operating characteristic (SROC) curve for combining information on a diagnostic test from several different studies. Unlike previous methods that assume the reference standard to be error free, our approach allows for the possibility of errors in the reference standard, through use of a latent class model. The model provides estimates of the sensitivity and specificity of the diagnostic test and the case prevalence in each study; these parameters can then be used in a meta-analysis, for example, using the regression method proposed by Moses et al., of a measure of test discrimination on a measure of the diagnostic threshold, to fit the SROC. The method is illustrated with an example on Pap smears that shows how adjusting for imperfection in the reference standard typically reduces the scatter of data in the SROC plot, and tends to indicate better performance of the test than otherwise.     

Estimating diagnostic accuracy of multiple binary tests with an imperfect reference standard

The goal in diagnostic medicine is often to estimate the diagnostic accuracy of multiple experimental tests relative to a gold standard reference. When a gold standard reference is not available, investigators commonly use an imperfect reference standard. This paper proposes methodology for estimating the diagnostic accuracy of multiple binary tests with an imperfect reference standard when information about the diagnostic accuracy of the imperfect test is available from external data sources. We propose alternative joint models for characterizing the dependence between the experimental tests and discuss the use of these models for estimating individual‐test sensitivity and specificity as well as prevalence and multivariate post‐test probabilities (predictive values). We show using analytical and simulation techniques that, as long as the sensitivity and specificity of the imperfect test are high, inferences on diagnostic accuracy are robust to misspecification of the joint model. The methodology is demonstrated with a study examining the diagnostic accuracy of various HIV‐antibody tests for HIV. Published in 2008 by John Wiley & Sons, Ltd.     

A tutorial in estimating the prevalence of disease in humans and animals in the absence of a gold standard diagnostic

Abstract

Epidemiological methods for estimating disease prevalence in humans and other animals in the absence of a gold standard diagnostic test are well established. Despite this, reporting apparent prevalence is still standard practice in public health studies and disease control programmes, even though apparent prevalence may differ greatly from the true prevalence of disease. Methods for estimating true prevalence are summarized and reviewed. A computing appendix is also provided which contains a brief guide in how to easily implement some of the methods presented using freely available software.