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从贝叶斯视角评估三种依赖培养的李斯特菌检测方法的诊断准确性。

Estimating the diagnostic accuracy of three culture-dependent methods for the Listeria monocytogenes detection from a Bayesian perspective.

机构信息

Laboratory of Food Quality Control and Hygiene, Department of Food Science and Technology, Agricultural University of Athens, Iera Odos 75, GR-118 55 Athens, Greece.

出版信息

Int J Food Microbiol. 2012 May 15;156(2):181-5. doi: 10.1016/j.ijfoodmicro.2012.03.027. Epub 2012 Mar 30.

DOI:10.1016/j.ijfoodmicro.2012.03.027
PMID:22507629
Abstract

The objective of this study was to estimate the test accuracy measures (classification probabilities [CPs], predictive values [PVs], likelihood ratios [LRs] and area under receiving operating characteristic curve [AUC]) of three different culture-dependent methods, commonly used during routine analysis for the detection of the foodborne pathogen Listeria monocytogenes, from a Bayesian perspective. Data from a previous study by Andritsos et al. (2010) were used to define measures of accuracy for the diagnostic tests. Samples of minced pork meat obtained from local markets were tested for L. monocytogenes presence by parallel testing using selective media (PALCAM, ALOA and RAPID'L.mono). Dirichlet distribution, which is the multivariate expression of a Beta distribution, was used to analyze the data. Bayesian analysis determines characteristics of the posterior distribution from available prior information. Results showed that all methods were best at ruling in L. monocytogenes presence than ruling it out. PALCAM seemed to have better performance based on positive PV, positive LR and AUC, but it was not so sensitive as RAPID'L.mono was. Results also showed that none of the media were perfect in detecting L. monocytogenes, i.e. sensitivity and specificity equal to one. Besides, the problem of observing zero counts may be overcome by applying Bayesian analysis, making the determination of a test performance feasible.

摘要

本研究旨在从贝叶斯的角度评估三种常用于常规分析以检测食源性病原体单核细胞增生李斯特菌的依赖培养方法的检测准确性衡量指标(分类概率[CP]、预测值[PV]、似然比[LR]和接收操作特征曲线下面积[AUC])。Andritsos 等人(2010 年)之前的研究数据用于定义诊断测试的准确性衡量指标。使用选择性培养基(PALCAM、ALOA 和 RAPID'L.mono)平行检测来自当地市场的绞碎猪肉样品,以检测单核细胞增生李斯特菌的存在。Dirichlet 分布是 Beta 分布的多元表达式,用于分析数据。贝叶斯分析从可用的先验信息确定后验分布的特征。结果表明,所有方法在判定单核细胞增生李斯特菌存在方面都优于排除其存在的方法。基于阳性 PV、阳性 LR 和 AUC,PALCAM 似乎具有更好的性能,但它不如 RAPID'L.mono 敏感。结果还表明,没有一种培养基能够完美地检测到单核细胞增生李斯特菌,即敏感性和特异性等于 1。此外,通过应用贝叶斯分析可以克服观察到零计数的问题,从而使测试性能的确定成为可能。

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