Trevethan Robert
Independent academic researcher and author, Albury, NSW, Australia.
Front Public Health. 2017 Nov 20;5:307. doi: 10.3389/fpubh.2017.00307. eCollection 2017.
Within the context of screening tests, it is important to avoid misconceptions about sensitivity, specificity, and predictive values. In this article, therefore, foundations are first established concerning these metrics along with the first of several aspects of pliability that should be recognized in relation to those metrics. Clarification is then provided about the definitions of sensitivity, specificity, and predictive values and why researchers and clinicians can misunderstand and misrepresent them. Arguments are made that sensitivity and specificity should usually be applied only in the context of describing a screening test's attributes relative to a reference standard; that predictive values are more appropriate and informative in actual screening contexts, but that sensitivity and specificity can be used for screening decisions about individual people if they are extremely high; that predictive values need not always be high and might be used to advantage by adjusting the sensitivity and specificity of screening tests; that, in screening contexts, researchers should provide information about all four metrics and how they were derived; and that, where necessary, consumers of health research should have the skills to interpret those metrics effectively for maximum benefit to clients and the healthcare system.
在筛查测试的背景下,避免对敏感性、特异性和预测值产生误解非常重要。因此,在本文中,首先要确立这些指标的基础,以及在这些指标方面应认识到的几个灵活性方面的第一个方面。然后对敏感性、特异性和预测值的定义以及研究人员和临床医生为何会误解和错误表述它们进行了说明。有人认为,敏感性和特异性通常仅应在描述筛查测试相对于参考标准的属性时使用;预测值在实际筛查背景中更合适且更具信息性,但如果敏感性和特异性极高,则可用于对个体进行筛查决策;预测值不一定总是很高,通过调整筛查测试的敏感性和特异性可能会有好处;在筛查背景下,研究人员应提供所有四个指标的信息以及它们是如何得出的;并且在必要时,健康研究的消费者应具备有效解释这些指标的技能,以使客户和医疗保健系统获得最大利益。