囊性纤维化的最佳基因筛选

Oper. Res. Pub Date : 2021-11-16 DOI:10.1287/opre.2021.2134
Hussein El Hajj, D. R. Bish, E. Bish
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引用次数: 1

摘要

对新生儿进行威胁生命的遗传病筛查是一项重要的公共卫生举措。囊性纤维化是这方面最普遍的疾病之一。作为囊性纤维化筛查过程的一部分,美国所有州都使用多种检测,包括检测导致囊性纤维化的300多种遗传变异(特定突变)中的一个子集的基因检测。El-Hajj、dr . Bish和E.K. Bish在“囊性纤维化的最佳基因筛查”一篇文章中,考虑到分类准确性和检测成本之间的权衡,以及限制所选变异数量的技术限制,开发了一个决策支持模型来选择筛选哪些遗传变异。由于变异患病率具有高度的不确定性,因此开发了一个鲁棒优化框架。进一步,分析比较了两种常用的囊性纤维化筛查方法,并确定了每种方法占主导地位的条件。提供了一个基于已发表数据的案例研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimal Genetic Screening for Cystic Fibrosis
Improving Newborn Screening for Genetic Diseases Screening newborns for life-threatening genetic diseases is an important public health initiative. Cystic fibrosis is one of the most prevalent diseases in this context. As part of the cystic fibrosis screening process, all states in the United States use multiple tests, including genetic tests that detect a subset of the more than 300 genetic variants (specific mutations) that cause cystic fibrosis. In “Optimal Genetic Screening for Cystic Fibrosis,” El-Hajj, D.R. Bish, and E.K. Bish develop a decision support model to select which genetic variants to screen for, considering the trade-off between classification accuracy and testing cost, and the technological constraints that limit the number of variants selected. Because variant prevalence rates are highly uncertain, a robust optimization framework is developed. Further, two commonly used cystic fibrosis screening processes are analytically compared, and conditions under which each process dominates are established. A case study based on published data are provided.
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