Peirce J C, Cornell R G
Department of Medical Education and Research, Good Samaritan Regional Medical Center, Phoenix, Arizona 85006.
Med Decis Making. 1993 Apr-Jun;13(2):141-51. doi: 10.1177/0272989X9301300208.
Data used to construct receiver operating characteristic (ROC) curves and to calculate the area under the curve (ROC AUC) can be used to derive stratum-specific likelihood ratios (SSLRs) with their 95% confidence intervals (95% CIs). The purpose of this study was to determine whether useful information can be obtained by adding SSLRs to the analysis of ROC curves. The authors analyzed four previously reported sets of data: 1) serum creatine kinase (SCK) for diagnosing acute myocardial infarction (AMI) in the coronary care unit (CCU); 2) SCK in the evaluation of chest pain in the emergency center (EC); 3) four predictor variables in the diagnosis of strep throat; and 4) the ordinal assessment of computed tomographic (CT) images. Use of SCK in the CCU produced four strata that had posttest probabilities that were highly discriminating, whereas SCK in the EC resulted in only two strata with limited discriminating ability. In either study the cutpoint at which the SSLR changed from less than to greater than 1.0 was higher than the reported upper normal for the test, thereby quantitating spectrum bias. The maximum number of strata of predictor signs and symptoms for strep throat was three rather than the five used in previous studies. With a larger sample size or pooling, four strata could probably be developed. With CT images, "definitely normal," "probably normal," and "questionable" were collapsed to one negative stratum. "Probably abnormal" became the true "questionable" stratum and "definitely abnormal" was the only positive stratum. The authors conclude that additional useful information is obtained by deriving stratum-specific likelihood ratios as part of the analysis of an ROC curve.
用于构建受试者工作特征（ROC）曲线及计算曲线下面积（ROC AUC）的数据，可用于推导特定分层似然比（SSLRs）及其95%置信区间（95% CIs）。本研究的目的是确定在ROC曲线分析中加入SSLRs是否能获得有用信息。作者分析了四组先前报道的数据：1）冠心病监护病房（CCU）中用于诊断急性心肌梗死（AMI）的血清肌酸激酶（SCK）；2）急诊中心（EC）中用于评估胸痛的SCK；3）诊断链球菌性咽炎的四个预测变量；4）计算机断层扫描（CT）图像的有序评估。在CCU中使用SCK产生了四个分层，其检验后概率具有高度区分性，而在EC中使用SCK仅产生了两个区分能力有限的分层。在任何一项研究中，SSLR从小于1.0变为大于1.0的切点均高于该检验报告的正常上限，从而量化了谱偏倚。链球菌性咽炎预测体征和症状的最大分层数为三个，而非先前研究中使用的五个。样本量增大或合并数据后，可能会形成四个分层。对于CT图像，“肯定正常”“可能正常”和“可疑”合并为一个阴性分层。“可能异常”成为真正的“可疑”分层，“肯定异常”是唯一的阳性分层。作者得出结论，作为ROC曲线分析的一部分，推导特定分层似然比可获得额外的有用信息。
