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敏感性、特异性、受试者工作特征(ROC)曲线及似然比:解读诊断试验的性能

Sensitivity, specificity, receiver-operating characteristic (ROC) curves and likelihood ratios: communicating the performance of diagnostic tests.

作者信息

Florkowski Christopher M

机构信息

Canterbury Health Laboratories, Christchurch, New Zealand.

出版信息

Clin Biochem Rev. 2008 Aug;29 Suppl 1(Suppl 1):S83-7.

Abstract
  • Diagnostic accuracy studies address how well a test identifies the target condition of interest. * Sensitivity, specificity, predictive values and likelihood ratios (LRs) are all different ways of expressing test performance. * Receiver operating characteristic (ROC) curves compare sensitivity versus specificity across a range of values for the ability to predict a dichotomous outcome. Area under the ROC curve is another measure of test performance. * All of these parameters are not intrinsic to the test and are determined by the clinical context in which the test is employed. * High sensitivity corresponds to high negative predictive value and is the ideal property of a "rule-out" test. * High specificity corresponds to high positive predictive value and is the ideal property of a "rule-in" test. * LRs leverage pre-test into post-test probabilities of a condition of interest and there is some evidence that they are more intelligible to users.
摘要
  • 诊断准确性研究关注一项检测识别目标疾病的能力有多强。

  • 灵敏度、特异度、预测值和似然比(LRs)都是表达检测性能的不同方式。

  • 受试者工作特征(ROC)曲线比较在一系列值范围内预测二分结果能力的灵敏度与特异度。ROC曲线下面积是检测性能的另一种度量。

  • 所有这些参数并非检测本身所固有,而是由检测所应用的临床背景决定。

  • 高灵敏度对应高阴性预测值,是“排除”检测的理想特性。

  • 高特异度对应高阳性预测值,是“纳入”检测的理想特性。

  • 似然比将检测前感兴趣疾病的概率转化为检测后概率,并且有证据表明它们对使用者来说更易懂。

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