Greiner M, Sohr D, Göbel P
Institute for Parasitology and Tropical Veterinary Medicine, Free University of Berlin, Germany.
J Immunol Methods. 1995 Sep 11;185(1):123-32. doi: 10.1016/0022-1759(95)00121-p.
A total number of 50 sera from clinically confirmed cases of canine Borrelia (B.) burgdorferi infection and 44 negative control sera were tested with a B. burgdorferi specific antibody ELISA. The data were submitted to the 'two-graph receiver operating characteristic' (TG-ROC) analysis which is a plot of the test sensitivity (Se) and specificity (Sp) against the threshold (cut-off) value assuming the latter to be an independent variable. Thus, in contrast to the conventional ROC analysis, valid pairs of Se and Sp can be read for pre-assigned threshold values directly from the TG-ROC plots. A cut-off that realises equal test parameters (Se = Sp = theta 0 (theta-zero)) can be obtained as the intersection point of the two graphs. Since the value for theta 0 is below a preselected accuracy level (95% or 90%), two cut-off values are selected that represent the bounds of an 'intermediate range' (IR). IR can be considered as a 'borderline' range for the clinical interpretation of test results. The proportion of the measurement range (MR) that gives unambiguous test results can be expressed using IR as the 'valid range proportion' (VRP = (MR-IR)/MR). VRP and theta 0 are useful parameters for test comparison since they do not depend upon the selection of a single cut-off point. In addition, the selection of cut-off values is supported by graphical displays of efficiency, Youden's index and likelihood ratios which can be considered as functions of the pre-assigned cut-off value. TG-ROC was derived as a user-defined template for a commercially available spreadsheet programme (MS-EXCEL, Microsoft).
使用伯氏疏螺旋体特异性抗体酶联免疫吸附测定法（ELISA）检测了50份临床确诊的犬伯氏疏螺旋体感染病例的血清以及44份阴性对照血清。将数据提交至“双图受试者工作特征”（TG-ROC）分析，该分析是将检测灵敏度（Se）和特异性（Sp）相对于阈值（临界值）作图，假设后者为自变量。因此，与传统的ROC分析不同，可以直接从TG-ROC图中读取针对预先设定阈值的有效Se和Sp对。实现相等检测参数（Se = Sp = θ0（θ零））的临界值可作为两条曲线的交点获得。由于θ0值低于预先选定的准确度水平（95%或90%），因此选择两个临界值，它们代表“中间范围”（IR）的界限。IR可被视为检测结果临床解释的“边界”范围。给出明确检测结果的测量范围（MR）比例可用IR表示为“有效范围比例”（VRP = (MR - IR)/MR）。VRP和θ0是用于检测比较的有用参数，因为它们不依赖于单个临界值的选择。此外，临界值的选择得到效率、约登指数和似然比的图形显示的支持，这些可被视为预先设定临界值的函数。TG-ROC是作为市售电子表格程序（MS-EXCEL，微软公司）的用户定义模板推导出来的。
