1 Department of Statistics and OR, Complutense University of Madrid, Madrid, Spain.
2 School of Agricultural Sciences, Laboratory of Biometry, University of Thessaly, Volos, Greece.
Stat Methods Med Res. 2019 May;28(5):1564-1578. doi: 10.1177/0962280218769334. Epub 2018 Apr 11.
Assessment of the diagnostic accuracy of biomarkers through receiver operating characteristic curve analysis frequently involves a limit of detection imposed by the laboratory analytical system precision. As a consequence, measurements below a certain level are undetectable and ignoring these is known to lead to negatively biased estimates of the area under the receiver operating characteristic curve. In this article, we introduce two receiver operating characteristic curve-based parametric approaches that tackle the issue of correct assessment of diagnostic markers in the presence of a limit of detection. Proposed approaches are simulation-based utilising bootstrap methodology. Non-parametric alternatives that are naively used in the literature do not solve the inherent problem of limit of detection values which are treated as censored observations. However, the latter seems to perform adequately well in our simulation study. Nonparametric bootstrap was consistently used throughout, while other bootstrap alternatives performed similarly in our pilot simulation study. The simulation study involves the comparison of parametric and non-parametric options described here versus alternative strategies that are routinely used in the literature. We apply all methods to a study-setting resembling a chemical quasi-standard situation, where compound tumour biomarkers were searched within a multi-variable set of measurements to discriminate between two groups, namely colorectal cancer and controls. We focus in the assessment of glutamine and methionine.
通过接收者操作特征曲线分析评估生物标志物的诊断准确性时，通常会受到实验室分析系统精度的检测限限制。因此，低于某个水平的测量值是无法检测到的，如果忽略这些值，就会导致接收者操作特征曲线下面积的估计值出现负偏。在本文中，我们引入了两种基于接收者操作特征曲线的参数方法，用于解决存在检测限的情况下正确评估诊断标志物的问题。提出的方法是基于模拟的，利用自举方法。文献中简单使用的非参数替代方法并不能解决检测限值的固有问题，这些值被视为删失观测值。然而，在我们的模拟研究中，后者似乎表现得相当好。整个模拟研究都使用了非参数自举，而其他自举替代方法在我们的初步模拟研究中表现相似。模拟研究涉及对这里描述的参数和非参数选项与文献中常用的替代策略进行比较。我们将所有方法应用于类似于化学准标准情况的研究环境中，在该环境中，在多变量测量集中搜索化合物肿瘤生物标志物，以区分两组，即结直肠癌和对照组。我们重点关注谷氨酰胺和蛋氨酸的评估。
