计算指数控制方法的性能特征用于phi多分析试验与算法分析
Radwa Ewaisha1,2, Tifani L Flieth1, Karl M Ness1
1Division of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, United States.
The journal of applied laboratory medicine
|November 8, 2024
概括
前列腺健康指数 (phi) 的质量控制需要改进. 一个新的计算phi QC指标 (PHIc) 更好地监测测定精度和偏差,提高疾病风险评分的可靠性.
科学领域:
- 临床化学 临床化学
- 生物医学诊断 生物医学诊断
- 前列腺癌生物标志物 前列腺癌生物标志物
背景情况:
- 像前列腺健康指数 (phi) 这样的算法分析 (MAAA) 的多分析分析对疾病风险评分至关重要.
- 对于phi的当前质量控制 (QC) 评估了个别组件,可能缺失了整体指数的不精确性和偏差.
- 这种间接的QC可能无法充分确保计算的多组件phi值的可靠性.
研究的目的:
- 评估前列腺健康指数 (phi) 与其单个组件相比的精度和偏差.
- 引入和评估一种新的计算phi QC指标 (PHIc),以改善MAAA绩效的监测.
- 用Westgard规则来确定PHIc与单个组件的质量控制失败频率.
主要方法:
- 比较测试间和测试内phi精度与单个组件测试精度.
- 开发了使用总PSA,自由PSA和p2PSA的QC数据计算的phi QC指标 (PHIc).
- 分析了PHIc QC失败率与单个组件QC失败率 (Westgard 13S,22S) 的比较,并检查了PHIc上的偏差影响.
主要成果:
- 平均测量phi不精确度 (6.7%CV) 显著高于单个组件不精确度 (3.9-4.5%CV).
- 追溯分析84个QC确定显示,基于用于Westgard规则的标准偏差的PHIc和组件的不同故障模式.
- 在组件测定中的模拟偏差表明PHIc指标的非线性变化.
结论:
- 建议使用额外的计算phi QC测量 (PHIc) 来有效监测MAAA的精度和偏差.
- 计算指数控制提供了一个可用于其他MAAA指数的补充QC方法.
- 实施PHIc可以提高从MAAAs获得的疾病风险得分的准确性和可靠性.
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