Diagnostic evaluation of pharmacokinetic features of functional markers.
Diagnostic evaluation of pharmacokinetic features of functional markers.
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功能标记物药代动力学特征的诊断评价。
DOI：
10.1080/10543406.2022.2148163
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发表时间：
2023
影响因子：
1.1
通讯作者：
Manatunga,Amita
中科院分区：
文献类型：
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作者：
Jang,JeongHoon;Manatunga,Amita
来自现代临床研究的功能（曲线）标志物的动态性为复杂的疾病生理学提供了更深入的见解。一种常见的临床实践是检查功能标志物的各种“药代动力学特征”（定积分、最大值、达到最大值的时间等）。反映了重要的生理基础。例如，目前肾梗阻的诊断程序是检查表征肾功能的肾图曲线的几个药代动力学特征。受这些临床实践的启发，我们开发了一个统计框架，用于使用受试者工作特征曲线下面积（AUC）评估药代动力学特征的诊断准确性。主要的挑战是在离散的时间点观察功能标志物，测量误差。为了解决这一挑战，我们开发了一个两阶段的非参数AUC估计的基础上汇总泛函提供统一的表示各种药代动力学特征，并研究其渐近性质。我们还提出了一个合理的适应半参数回归模型，可以描述不同亚群的AUC异质性，同时适当地处理离散性和噪音观察到的功能标志物。在这里，介绍了一种新的数据驱动的方法，该方法在回归系数估计的偏差和效率之间进行平衡。最后，该框架被应用于严格评估肾图曲线的药代动力学特征，可能用于检测肾梗阻。
The dynamicity of functional (curve) markers from modern clinical studies offers deeper insights into complex disease physiology. A frequent clinical practice is to examine various ‘pharmacokinetic features’ of functional markers (definite integral, maximum value, time to maximum, etc.) that reflect important physiological underpinnings. For instance, the current diagnostic procedure for kidney obstruction is to examine several pharmacokinetic features of renogram curves characterizing renal function. Motivated by such clinical practices, we develop a statistical framework for evaluating diagnostic accuracy of pharmacokinetic features using area under the receiver operating characteristic curve (AUC). The major challenge is that functional markers are observed at discrete time points with measurement error. To address this challenge, we develop a two-stage non-parametric AUC estimator based on summary functionals providing unified representation of various pharmacokinetic features and study its asymptotic properties. We also propose a sensible adaptation of a semiparametric regression model that can describe heterogeneity of AUC across different subpopulations, while appropriately handling discreteness and noise in observed functional markers. Here, a novel data-driven approach that balances between bias and efficiency of the regression coefficient estimates is introduced. Finally, the framework is applied to rigorously evaluate pharmacokinetic features of renogram curves potentially useful for detecting kidney obstruction.