Kelly H, Bull A, Russo P, McBryde E S
Victorian Infectious Diseases Reference Laboratory, Carlton South, Melbourne, Australia.
J Hosp Infect. 2008 Jun;69(2):164-8. doi: 10.1016/j.jhin.2008.02.021. Epub 2008 Apr 29.
Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) are terms usually associated with diagnostic testing. Although these concepts have been expanded from diagnostic assays to surveillance systems, these systems are not like diagnostic assays. In attempting to estimate the sensitivity and specificity of surveillance systems, situations may arise where only the PPV, NPV and prevalence are known. We aim to demonstrate the equivalence of two methods for calculating sensitivity and specificity from PPV, NPV and prevalence. The formulae for sensitivity and specificity are calculated from first principles and compared with the adjustment of a standard contingency table. We have illustrated this method using a review of a sample of surgical site infection cases following coronary artery bypass grafting. The derived prevalence from the sample is an estimate of the population prevalence and is the value that must be used in the formulae for sensitivity and specificity as functions of PPV, NPV and prevalence to obtain the same estimates as those obtained from the adjusted contingency table. The general proof of this principle is provided as an Appendix. The sensitivity and specificity of surveillance systems can be calculated by two equivalent methods when only PPV, NPV and prevalence are known.
敏感性、特异性、阳性预测值（PPV）和阴性预测值（NPV）是通常与诊断检测相关的术语。尽管这些概念已从诊断检测扩展到监测系统，但这些系统与诊断检测不同。在试图估计监测系统的敏感性和特异性时，可能会出现仅知道PPV、NPV和患病率的情况。我们旨在证明从PPV、NPV和患病率计算敏感性和特异性的两种方法的等效性。敏感性和特异性的公式从基本原理推导得出，并与标准列联表的调整进行比较。我们通过回顾冠状动脉搭桥术后手术部位感染病例的样本来说明这种方法。从样本得出的患病率是总体患病率的估计值，并且是在敏感性和特异性公式中作为PPV、NPV和患病率的函数使用的值，以获得与从调整后的列联表获得的估计值相同的估计值。该原理的一般证明作为附录提供。当仅知道PPV、NPV和患病率时，监测系统的敏感性和特异性可以通过两种等效方法计算。
