Le C T
School of Public Health and Cancer Center, University of Minnesota, Minneapolis 55455, USA.
Biometrics. 1997 Sep;53(3):998-1007.
In many clinical studies, it is clear that external forces can affect the performance of diagnostic tests, as these factors influence the distributions of separator variables. A new estimator for the receiver operating characteristic (ROC) function is proposed; this estimator converges to the ROC function uniformly on the interval [0,1]. Using this new estimator, the author proposes to use Cox's proportional hazards regression model for the evaluation of confounding effects in ROC studies. The method can be used even when concomitant information is only available for the cases, for example, disease severity. A textbook example on prostate cancer is described for illustration.
在许多临床研究中，很明显外力会影响诊断测试的性能，因为这些因素会影响分隔变量的分布。本文提出了一种新的接收者操作特征（ROC）函数估计器；该估计器在区间[0,1]上一致收敛于ROC函数。利用这个新的估计器，作者建议使用Cox比例风险回归模型来评估ROC研究中的混杂效应。即使仅在病例中可获得伴随信息，例如疾病严重程度，该方法也可使用。文中描述了一个关于前列腺癌的典型例子以作说明。
