论文标题
小组测试是否可以在疾病鉴定方面进行黄金时段？
Is Group Testing Ready for Prime-time in Disease Identification?
论文作者
论文摘要
大规模疾病筛查是一个复杂的过程，在这种过程中，必须与紧迫的公共卫生需求保持平衡。当目标是筛查传染病时，一种方法是小组测试，其中最初在池中测试样品，并且只有在初始合并测试为阳性的情况下才能重新测试单个样品。直观地，如果感染的患病率很小，则可能导致所需的测试总数大幅减少。尽管如此，在医学研究中使用小组测试仍然有限，这在很大程度上是由于对合并对给定测定准确性的影响的怀疑。尽管有大量的研究解决了小组测试研究中测试错误的问题，但习惯假设错误分类参数是从外部人群中知道的，并且/或值不会随组规模而变化。这两个假设对于许多考虑小组测试在研究设计中的医生来说都是高度疑问的。在本文中，我们探讨了这些假设的失败如何影响小组测试设计的功效，因此，小组测试目前是否可用于医疗筛查。具体而言，我们研究在设计阶段对灵敏度函数的错误假设如何导致对过程的总体灵敏度和预期测试数量的估计不佳。此外，如果使用验证研究来估计给定测定法的汇总错误分类参数，我们表明所需的样本大小是如此之大，以至于除了最大的筛选程序外，
Large scale disease screening is a complicated process in which high costs must be balanced against pressing public health needs. When the goal is screening for infectious disease, one approach is group testing in which samples are initially tested in pools and individual samples are retested only if the initial pooled test was positive. Intuitively, if the prevalence of infection is small, this could result in a large reduction of the total number of tests required. Despite this, the use of group testing in medical studies has been limited, largely due to skepticism about the impact of pooling on the accuracy of a given assay. While there is a large body of research addressing the issue of testing errors in group testing studies, it is customary to assume that the misclassification parameters are known from an external population and/or that the values do not change with the group size. Both of these assumptions are highly questionable for many medical practitioners considering group testing in their study design. In this article, we explore how the failure of these assumptions might impact the efficacy of a group testing design and, consequently, whether group testing is currently feasible for medical screening. Specifically, we look at how incorrect assumptions about the sensitivity function at the design stage can lead to poor estimation of a procedure's overall sensitivity and expected number of tests. Furthermore, if a validation study is used to estimate the pooled misclassification parameters of a given assay, we show that the sample sizes required are so large as to be prohibitive in all but the largest screening programs
