Optimal sampling times in population pharmacokinetic studies

被引：25

作者：

Stroud, JR

Müller, P

Rosner, GL

机构：

[1] Univ Chicago, Dept Stat, Chicago, IL 60637 USA

[2] Duke Univ, Durham, NC USA

来源：

JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C-APPLIED STATISTICS | 2001年 / 50卷

关键词：

clinical trial; limited sampling strategies; longitudinal data; Markov chain Monte Carlo methods; optimal design; population model; random-effects regression;

D O I：

10.1111/1467-9876.00239

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

We propose a simulation-based approach to decision theoretic Bayesian optimal design. The underlying probability model is a population pharmacokinetic model which allows for correlated responses (drug concentrations) and patient-to-patient heterogeneity. We consider the problem of choosing sampling times for the anticancer agent paclitaxel, using criteria related to the total area under the curve, the time above a critical threshold and the sampling cost.

引用

页码：345 / 359

页数：15

共 38 条

[1] OPTIMUM EXPERIMENTAL-DESIGNS FOR PROPERTIES OF A COMPARTMENTAL MODEL [J].