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Application of statistical process control to qualitative molecular diagnostic assays

机译:统计过程控制在定性分子诊断分析中的应用

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摘要

Modern pathology laboratories and in particular high throughput laboratories such as clinical chemistry have developed a reliable system for statistical process control (SPC). Such a system is absent from the majority of molecular laboratories and where present is confined to quantitative assays. As the inability to apply SPC to an assay is an obvious disadvantage this study aimed to solve this problem by using a frequency estimate coupled with a confidence interval calculation to detect deviations from an expected mutation frequency. The results of this study demonstrate the strengths and weaknesses of this approach and highlight minimum sample number requirements. Notably, assays with low mutation frequencies and detection of small deviations from an expected value require greater sample numbers to mitigate a protracted time to detection. Modeled laboratory data was also used to highlight how this approach might be applied in a routine molecular laboratory. This article is the first to describe the application of SPC to qualitative laboratory data.
机译:现代病理学实验室,特别是高通量实验室,例如临床化学,已经开发出可靠的统计过程控制(SPC)系统。大多数分子实验室都没有这种系统,并且该系统仅限于定量分析。由于无法将SPC应用于检测是一个明显的缺点,因此本研究旨在通过使用频率估计和置信区间计算来检测与预期突变频率的偏差来解决此问题。这项研究的结果证明了这种方法的优点和缺点,并强调了最低样本数量要求。值得注意的是,具有低突变频率的检测和与期望值的小偏差检测需要更大的样本数,以减少检测时间延长。建模的实验室数据还用于强调这种方法如何在常规分子实验室中应用。本文是第一篇描述SPC在定性实验室数据中的应用的文章。

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