贝叶斯潜在类别模型在疟疾诊断中的应用。
Bayesian Latent Class Models in malaria diagnosis.
机构信息
CEAUL and Unidade de Saúde Pública Internacional e Bioestatística, Instituto de Higiene e Medicina Tropical, Universidade Nova de Lisboa, Lisboa, Portugal.
出版信息
PLoS One. 2012;7(7):e40633. doi: 10.1371/journal.pone.0040633. Epub 2012 Jul 23.
AIMS
The main focus of this study is to illustrate the importance of the statistical analysis in the evaluation of the accuracy of malaria diagnostic tests, without admitting a reference test, exploring a dataset (n=3317) collected in São Tomé and Príncipe.
METHODS
Bayesian Latent Class Models (without and with constraints) are used to estimate the malaria infection prevalence, together with sensitivities, specificities, and predictive values of three diagnostic tests (RDT, Microscopy and PCR), in four subpopulations simultaneously based on a stratified analysis by age groups (< 5, ≥ 5 years old) and fever status (febrile, afebrile).
RESULTS
In the afebrile individuals with at least five years old, the posterior mean of the malaria infection prevalence is 3.2% with a highest posterior density interval of [2.3-4.1]. The other three subpopulations (febrile ≥ 5 years, afebrile or febrile children less than 5 years) present a higher prevalence around 10.3% [8.8-11.7]. In afebrile children under-five years old, the sensitivity of microscopy is 50.5% [37.7-63.2]. In children under-five, the estimated sensitivities/specificities of RDT are 95.4% [90.3-99.5]/93.8% [91.6-96.0]--afebrile--and 94.1% [87.5-99.4]/97.5% [95.5-99.3]--febrile. In individuals with at least five years old are 96.0% [91.5-99.7]/98.7% [98.1-99.2]--afebrile--and 97.9% [95.3-99.8]/97.7% [96.6-98.6]--febrile. The PCR yields the most reliable results in four subpopulations.
CONCLUSIONS
The utility of this RDT in the field seems to be relevant. However, in all subpopulations, data provide enough evidence to suggest caution with the positive predictive values of the RDT. Microscopy has poor sensitivity compared to the other tests, particularly, in the afebrile children less than 5 years. This type of findings reveals the danger of statistical analysis based on microscopy as a reference test. Bayesian Latent Class Models provide a powerful tool to evaluate malaria diagnostic tests, taking into account different groups of interest.
目的
本研究的主要重点是说明在评估疟疾诊断测试的准确性时进行统计分析的重要性，不承认参考测试，探索在圣多美和普林西比收集的数据集（n=3317）。
方法
使用贝叶斯潜在类别模型（无约束和有约束）来估计疟疾感染率，同时根据年龄组（<5 岁，≥5 岁）和发热状态（发热、不发热）进行分层分析，同时估计三种诊断测试（RDT、显微镜和 PCR）的敏感性、特异性和预测值。
结果
在≥5 岁且不发热的个体中，疟疾感染率的后验均值为 3.2%，最高后验密度区间为[2.3-4.1]。其他三个亚组（≥5 岁发热、≥5 岁不发热或发热儿童<5 岁）的流行率约为 10.3%[8.8-11.7]。在<5 岁不发热的儿童中，显微镜的敏感性为 50.5%[37.7-63.2]。在<5 岁的儿童中，RDT 的估计敏感性/特异性分别为 95.4%[90.3-99.5]/93.8%[91.6-96.0]--不发热--和 94.1%[87.5-99.4]/97.5%[95.5-99.3]--发热。在≥5 岁的个体中为 96.0%[91.5-99.7]/98.7%[98.1-99.2]--不发热--和 97.9%[95.3-99.8]/97.7%[96.6-98.6]--发热。PCR 在四个亚组中产生最可靠的结果。
结论
这种 RDT 在现场似乎具有实用性。然而，在所有亚组中，数据提供了足够的证据表明，对于 RDT 的阳性预测值，需要谨慎。与其他测试相比，显微镜的敏感性较差，尤其是在<5 岁的不发热儿童中。这种类型的发现揭示了基于显微镜作为参考测试的统计分析的危险性。贝叶斯潜在类别模型为评估疟疾诊断测试提供了一种强大的工具，同时考虑了不同的感兴趣群体。
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