Mazumdar Madhu, Liu Aiyi
Department of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, 1275 York Avenue, New York, NY 10021, USA.
Stat Med. 2003 Mar 15;22(5):727-39. doi: 10.1002/sim.1386.
In the field of diagnostic medicine, comparative clinical trials are necessary for assessing the utility of one diagnostic test over another. The area under the receiver operating characteristic (ROC) curve, commonly referred to as AUC, is a general measure of a test's inherent ability to distinguish between patients with and without a condition. Standardized AUC difference is the most frequently used statistic for comparing two diagnostic tests. In therapeutic comparative clinical trials with sequential patient entry, fixed sample design (FSD) is unjustified on ethical and economical grounds and group sequential design (GSD) is frequently used. In this paper, we argue that the same reasoning exists for the comparative clinical trials in diagnostic medicine and hence GSD should be utilized in this field for designing trials. Since computation of the stopping boundaries of GSD and data analysis after a group sequential test rely heavily on Brownian motion approximation, we derive the asymptotic distribution of the standardized AUC difference statistic and point out its resemblance to the Brownian motion. Boundary determination and sample size calculation are then illustrated through an example from a cancer clinical trial.
在诊断医学领域,比较性临床试验对于评估一种诊断测试相对于另一种诊断测试的效用是必要的。受试者工作特征(ROC)曲线下的面积,通常称为AUC,是衡量测试区分患病和未患病患者的内在能力的一般指标。标准化AUC差异是比较两种诊断测试最常用的统计量。在有连续患者入组的治疗性比较临床试验中,固定样本设计(FSD)在伦理和经济方面是不合理的,因此经常使用成组序贯设计(GSD)。在本文中,我们认为诊断医学中的比较性临床试验也存在同样的道理,因此在该领域设计试验时应采用GSD。由于GSD停止边界的计算以及成组序贯检验后的数据分析严重依赖布朗运动近似,我们推导了标准化AUC差异统计量的渐近分布,并指出其与布朗运动的相似性。然后通过一个癌症临床试验的例子来说明边界确定和样本量计算。