Department of Biostatistics and Data Science, University of Kansas Medical Center, Kansas City, KS, USA.
Stat Methods Med Res. 2024 Sep;33(9):1577-1594. doi: 10.1177/09622802241267356. Epub 2024 Aug 8.
measures of biomarker accuracy that employ the receiver operating characteristic surface have been proposed for biomarkers that classify patients into one of three groups: healthy, benign, or aggressive disease. The volume under the receiver operating characteristic surface summarizes the overall discriminatory ability of a biomarker in such configurations, but includes cutoffs associated with clinically irrelevant true classification rates. Due to the lethal nature of pancreatic cancer, cutoffs associated with a low true classification rate for identifying patients with pancreatic cancer may be undesirable and not appropriate for use in a clinical setting. In this project, we study the properties of a more focused criterion, the partial volume under the receiver operating characteristic surface, that summarizes the diagnostic accuracy of a marker in the three-class setting for regions restricted to only those of clinical interest. We propose methods for estimation and inference on the partial volume under the receiver operating characteristic surface under parametric and non-parametric frameworks and apply these methods to the evaluation of potential biomarkers for the diagnosis of pancreatic cancer.
已经提出了用于将患者分为健康、良性或侵袭性疾病三组之一的生物标志物的准确性测量方法,该方法采用接收者操作特征曲面。在这种配置中,接收者操作特征曲面下的体积总结了生物标志物的整体判别能力,但包括与临床无关的真实分类率相关的截止值。由于胰腺癌的致命性质,与识别患有胰腺癌的患者的低真实分类率相关的截止值可能是不可取的,并且不适用于临床环境中使用。在这个项目中,我们研究了更集中的标准——接收者操作特征曲面下的部分体积的特性,该标准总结了在仅对临床感兴趣的区域进行限制的三分类设置中标记的诊断准确性。我们提出了在参数和非参数框架下估计和推断接收者操作特征曲面下的部分体积的方法,并将这些方法应用于评估诊断胰腺癌的潜在生物标志物。