Centralised and Point of Care Solutions, Roche Diagnostics GmbH, Penzberg, Germany.
Institute for Medical Information Processing, Biometry, and Epidemiology (IBE), Faculty of Medicine, Ludwig-Maximilians-University, Munich, Germany.
Stat Med. 2021 Jul 20;40(16):3645-3666. doi: 10.1002/sim.8987. Epub 2021 Apr 19.
In order to release correct biomarker results of a laboratory test, it is a regulatory requirement to apply quality control standards for controlling analytical errors. Releasing an incorrect test result might lead to wrong diagnosis or treatment of a patient in medical decision-making. In laboratory medicine, one of the means to control analytical errors is statistical process control procedures proposed by James O. Westgard and his coworkers nowadays known as "Westgard rules." To judge their performance for discriminating in-control from out-of-control processes, power curves are used. In this article, we describe functions for the power curves of the within-run Westgard rules. Based on these power curves, we use a benchmark approach for selecting a quality control procedure out of the set of Westgard rules. It is shown that two graphical procedures proposed by Westgard and his coworkers can be reduced to this benchmark approach. Besides, a commonly used measure in laboratory medicine for describing out-of-control processes is critically examined revealing the threat of selecting too optimistic quality control rules.
为了发布实验室检测的正确生物标志物结果，应用质量控制标准来控制分析误差是法规要求。在医疗决策中发布不正确的测试结果可能会导致对患者的错误诊断或治疗。在实验室医学中，控制分析误差的一种手段是由 James O. Westgard 和他的同事们提出的统计过程控制程序，现在称为“Westgard 规则”。为了判断它们在区分控制和失控过程中的性能，使用了功效曲线。在本文中，我们描述了运行内 Westgard 规则的功效曲线的函数。基于这些功效曲线，我们使用基准方法从 Westgard 规则集中选择质量控制程序。结果表明，Westgard 和他的同事们提出的两种图形程序可以简化为这种基准方法。此外，还对实验室医学中用于描述失控过程的常用方法进行了严格检查，揭示了选择过于乐观的质量控制规则的威胁。
