基于病毒载量进展和混合稀释的混合检测敏感性推导方法。
A methodology for deriving the sensitivity of pooled testing, based on viral load progression and pooling dilution.
机构信息
Grado Department of Industrial and Systems Engineering, Virginia Tech, Blacksburg, VA, 24061, USA.
Department of Industrial and Systems Engineering, Texas A&M University, College Station, TX, 77843, USA.
出版信息
J Transl Med. 2019 Aug 6;17(1):252. doi: 10.1186/s12967-019-1992-2.
BACKGROUND
Pooled testing, in which biological specimens from multiple subjects are combined into a testing pool and tested via a single test, is a common testing method for both surveillance and screening activities. The sensitivity of pooled testing for various pool sizes is an essential input for surveillance and screening optimization, including testing pool design. However, clinical data on test sensitivity values for different pool sizes are limited, and do not provide a functional relationship between test sensitivity and pool size. We develop a novel methodology to accurately compute the sensitivity of pooled testing, while accounting for viral load progression and pooling dilution. We demonstrate our methodology on the nucleic acid amplification testing (NAT) technology for the human immunodeficiency virus (HIV).
METHODS
Our methodology integrates mathematical models of viral load progression and pooling dilution to derive test sensitivity values for various pool sizes. This methodology derives the conditional test sensitivity, conditioned on the number of infected specimens in a pool, and uses the law of total probability, along with higher dimensional integrals, to derive pooled test sensitivity values. We also develop a highly accurate and easy-to-compute approximation function for pooled test sensitivity of the HIV ULTRIO Plus NAT Assay. We calibrate model parameters using published efficacy data for the HIV ULTRIO Plus NAT Assay, and clinical data on viral RNA load progression in HIV-infected patients, and use this methodology to derive and validate the sensitivity of the HIV ULTRIO Plus Assay for various pool sizes.
RESULTS
We demonstrate the value of this methodology through optimal testing pool design for HIV prevalence estimation in Sub-Saharan Africa. This case study indicates that the optimal testing pool design is highly efficient, and outperforms a benchmark pool design.
CONCLUSIONS
The proposed methodology accounts for both viral load progression and pooling dilution, and is computationally tractable. We calibrate this model for the HIV ULTRIO Plus NAT Assay, show that it provides highly accurate sensitivity estimates for various pool sizes, and, thus, yields efficient testing pool design for HIV prevalence estimation. Our model is generic, and can be calibrated for other infections.
背景
混合检测是一种常见的检测方法，即将多个个体的生物样本合并到一个检测池中，通过单次检测进行检测。混合检测对于各种池大小的敏感性是监测和筛查优化的重要输入，包括检测池设计。然而，不同池大小的检测敏感性的临床数据有限，并且不能提供检测敏感性与池大小之间的函数关系。我们开发了一种新的方法来准确计算混合检测的敏感性，同时考虑病毒载量的进展和混合稀释。我们使用核酸扩增检测（NAT）技术对人类免疫缺陷病毒（HIV）进行了方法验证。
方法
我们的方法将病毒载量进展和混合稀释的数学模型相结合，得出各种池大小的检测敏感性值。该方法推导出条件检测敏感性，即基于池中的感染样本数量的条件检测敏感性，并使用全概率定律以及更高维度的积分来推导出混合检测敏感性值。我们还开发了一种高度准确且易于计算的 HIV ULTRIO Plus NAT 检测的混合检测敏感性近似函数。我们使用发表的 HIV ULTRIO Plus NAT 检测功效数据和 HIV 感染者的病毒 RNA 载量进展的临床数据来校准模型参数，并使用该方法推导和验证各种池大小的 HIV ULTRIO Plus 检测的敏感性。
结果
我们通过 HIV 在撒哈拉以南非洲的流行率估计的最佳检测池设计展示了该方法的价值。该案例研究表明，最佳检测池设计非常高效，优于基准池设计。
结论
所提出的方法既考虑了病毒载量的进展，又考虑了混合稀释，并且计算上易于处理。我们为 HIV ULTRIO Plus NAT 检测校准了该模型，表明它可以为各种池大小提供高度准确的敏感性估计，从而为 HIV 流行率估计提供高效的检测池设计。我们的模型是通用的，可以为其他感染进行校准。
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