[ROC曲线:一般特征及其在临床实践中的有用性]
Ivonne Analí Roy-García1,2, Carlos Paredes-Manjarrez3, Jorge Moreno-Palacios4
1Instituto Mexicano del Seguro Social, Coordinación de Investigación en Salud, Centro de Adiestramiento e Investigación Clínica. Ciudad de México, México.
Revista medica del Instituto Mexicano del Seguro Social
|November 7, 2023
概括
接收器操作特征 (ROC) 曲线对于解释诊断测试结果和识别预后标记是必不可少的. 本指南解释了ROC曲线的基础知识,包括曲线下的面积 (AUC) 的解释和比较诊断测试性能.
科学领域:
- 医学诊断 医学诊断 医学诊断
- 生物统计学 生物统计学
- 临床流行病学临床流行病学
背景情况:
- 诊断测试通常会产生需要解释的数值结果.
- 确定值对于将结果分类为正常/异常和指导患者护理至关重要.
- 接收器运行特征 (ROC) 曲线是这个过程中的一个关键的统计工具.
研究的目的:
- 解释ROC曲线使用和解释的基本概念.
- 详细说明曲线下的面积 (AUC) 在评估测试性能中的重要性.
- 概述用于比较多个诊断测试的准确性方法.
主要方法:
- 描述ROC曲线的构造和解释.
- 曲线下的面积 (AUC) 的计算和含义的解释.
- 使用ROC分析比较诊断测试性能的方法.
主要成果:
- ROC曲线有助于选择诊断和预后变量的最佳切断点.
- AUC量化了测试的整体诊断准确性.
- ROC分析可以比较多个测试,以确定最精确的测试.
结论:
- ROC曲线是评估诊断测试性能和预后标记的多功能工具.
- 了解ROC分析对于准确的临床决策和测试选择至关重要.
- 该方法适用于各种疾病,包括COVID-19等传染病.
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