专注于诊断的准确性危及治疗的最佳性
Jack Dowie1,2, Mette Kjer Kaltoft2, Vije Kumar Rajput1,3
1London School of Hygiene and Tropical Medicine, London, UK.
Studies in health technology and informatics
|May 17, 2025
概括
选择顺序测试的截止值需要评估虚假警报和虚假保证之间的权衡. 我们的FARN指标可以透明地显示出这个错误率,帮助最佳的测试解释,以便更好地照顾患者.
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
- 心理测量 心理测量 心理测量
背景情况:
- 常规测试通常用于诊断和查.
- 截止界限选择通常依赖于最大限度地提高灵敏度和特异性,并平等对待错误.
- 这种方法忽略了虚假阳性和虚假阴性的差异性成本.
研究的目的:
- 引入每次虚假保证数 (FARN) 的虚假警报指标.
- 展示FARN如何透明地量化不同截止点的错误权衡.
- 倡导对FARN进行例行报告,以告知最佳切线选择.
主要方法:
- 定义FARN为虚假警报与虚假保证的比例.
- 在顺序测试中对所有可能的切断值计算FARN.
- 用GAD-7来检测通用焦虑障碍的方法.
主要成果:
- 现有的方法隐含嵌入错误权衡,没有透明度.
- FARN提供了一个清晰的量化衡量虚假警报和虚假保证之间的平衡.
- GAD-7的例子展示了FARN在理解切断影响方面的实际应用.
结论:
- 仅仅专注于诊断准确度指标,如灵敏度和特异性,可能会产生误导.
- 定期报告FARN对于在诊断和查测试中透明的切断界限选择至关重要.
- 考虑到不同类型错误的相对无用性,导致更适当的临床决策和治疗结果.
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