Rombach J J, Slotboom B J
Maturitas. 1985 May;7(1):31-41. doi: 10.1016/0378-5122(85)90032-5.
Assessment of the accuracy of diagnostic procedures has been made independent of the diagnostic criteria used by means of Relative Operating Characteristics (ROC) analysis. A ROC curve describes the mutual relationship between the sensitivity and specificity of a diagnostic decision on the basis of various diagnostic criteria. The construction of such ROC curves is made possible if diagnoses are graded into levels of certainty. The curve enables the choice of an operating point with predetermined sensitivity and specificity values for the diagnosis decision. The population-based breast-cancer and cervical cancer screening projects carried out in Utrecht demonstrated an excellent fit between actual data and the calculated ROC curves. Analysis of the accuracy or performance of cytological diagnosis uncovered a problem arising from the similarly graded histopathological reference criteria used to determine the 'truth' of the cytological diagnosis decisions. The proposed solution is a serial calculation of ROC curves, one for each level differentiating between the histopathological categories. The ensuing three-dimensional ROC hill may reveal a summit marking numerically advantageous diagnosis criterion levels for both the test and the disease to be detected, or a depression signalling locally below-standard detection performance.
诊断程序准确性的评估已通过相对操作特征（ROC）分析独立于所使用的诊断标准进行。ROC曲线描述了基于各种诊断标准的诊断决策的敏感性和特异性之间的相互关系。如果将诊断分为确定程度等级，那么构建此类ROC曲线是可行的。该曲线能够为诊断决策选择具有预定敏感性和特异性值的操作点。在乌得勒支开展的基于人群的乳腺癌和宫颈癌筛查项目表明，实际数据与计算出的ROC曲线拟合度极佳。对细胞学诊断准确性或性能的分析发现，用于确定细胞学诊断决策“真实性”的组织病理学参考标准分级相似会引发一个问题。建议的解决方案是对ROC曲线进行系列计算，针对区分组织病理学类别的每个级别计算一条曲线。由此产生的三维ROC山丘可能会显示一个顶点，标志着对于检测方法和待检测疾病在数值上有利的诊断标准级别，或者显示一个凹陷，表明局部检测性能未达标准。
