新医改政策背景下医院药品库存警戒限研究

目的:通过设定药品库存警戒限,高效合理控制医院药品库存,进而保障药品供应充足前提下控制成本.方法:分析库存药品成本组成,推导经济订货量(economic order quantity,EOQ)公式模型,根据历史库存数据,通过Crystalball软件蒙特卡罗模拟算法模拟药品库存警戒限,模拟次数设定为15 000次.结果...     

Dosimetric effect of set-up error in accelerator-based boron neutron capture therapy for head and neck cancer

The dosimetric effect of set-up error in boron neutron capture therapy (BNCT) for head and neck cancer remains unclear. In this study, we analyzed the tendency of dose error by treatment location when simulating the set-up error of patients. We also determined the tolerance level of the set-up error in BNCT for head and neck cancer. As a method, the distal direction was shifted with an interval of 2.5 mm, from 0.0 mm to +20.0 mm and compared with the dose at the reference position. Similarly, the horizontal direction and vertical direction were shifted, with an interval of 5.0 mm, from −20.0 mm to +20.0 mm. In addition, cases with 3.0 mm and 5.0 mm simultaneous shifts in all directions were analyzed as the worst-case scenario. The dose metrics of the minimum dose of the tumor and the maximum dose of the mucosa were evaluated. From unidirectional set-up error analysis, in most cases, the set-up errors with dose errors within ±5% were Δdistal < +2.5 mm, Δhorizontal < ±5.0 mm and Δvertical < ±5.0 mm. In the simulation of 3.0 mm shifts in all directions, the errors in the minimum tumor dose and maximum mucosal dose were −3.6% ±1.4% (range, −5.4% to −0.6%) and 2% ±1.4% (range, 0.4% to 4.5%), respectively. From these results, if the set-up error was within ±3.0 mm in each direction, the dose errors of the tumor and mucosa could be suppressed within approximately ±5%, which is suggested as a tolerance level.     

An automated process for building reliable and optimal in vitro/in vivo correlation models based on Monte Carlo simulations

Many mathematical models have been proposed for establishing an in vitro/in vivo correlation (IVIVC). The traditional IVIVC model building process consists of 5 steps: deconvolution, model fitting, convolution, prediction error evaluation, and cross-validation. This is a time-consuming process and typically a few models at most are tested for any given data set. The objectives of this work were to (1) propose a statistical tool to screen models for further development of an IVIVC, (2) evaluate the performance of each model under different circumstances, and (3) investigate the effectiveness of common statistical model selection criteria for choosing IVIVC models. A computer program was developed to explore which model(s) would be most likely to work well with a random variation from the original formulation. The process used Monte Carlo simulation techniques to build IVIVC models. Data-based model selection criteria (Akaike Information Criteria [AIC], R2) and the probability of passing the Food and Drug Administration "prediction error" requirement was calculated. To illustrate this approach, several real data sets representing a broad range of release profiles are used to illustrate the process and to demonstrate the advantages of this automated process over the traditional approach. The Hixson-Crowell and Weibull models were often preferred over the linear. When evaluating whether a Level A IVIVC model was possible, the model selection criteria AIC generally selected the best model. We believe that the approach we proposed may be a rapid tool to determine which IVIVC model (if any) is the most applicable.     

Fuzzy Simulation of Pharmacokinetic Models: Case Study of Whole Body Physiologically Based Model of Diazepam

The aim of the present study is to develop and implement a methodology that accounts for parameter variability and uncertainty in the presence of qualitative and semi-quantitative information (fuzzy simulations) as well as when some parameters are better quantitatively defined than others (fuzzy-probabilistic approach). The fuzzy simulations method consists of (i) representing parameter uncertainty and variability by fuzzy numbers and (ii) simulating predictions by solving the pharmacokinetic model. The fuzzy-probabilistic approach includes an additional transformation between fuzzy numbers and probability density functions. To illustrate the proposed method a diazepam WBPBPK model was used where the information for hepatic intrinsic clearance determined by in vitro-in vivo scaling was semi-quantitative. The predicted concentration time profiles were compared with those resulting from a Monte Carlo simulation. Fuzzy simulations can be used as an alternative to Monte Carlo simulation.     

基于蒙特卡洛的中美药典含量均匀度检查法的比较研究

目的 利用蒙特卡洛方法比较研究中国药典和美国药典的含量均匀度检查法,并提出改进思路。方法 以含量均匀度检查法准确率为性能指标,采用蒙特卡洛方法模拟药品质量的变化,并进行模拟抽样检查,比较中美药典含量均匀度检查法的性能;通过中心复合实验设计,考察中美药典含量均匀度检查法的检查参数对准确率的影响。结果 在不同均值和标准差情况下,中美药典的检查准确率无显著差异;中心复合实验设计的结果表明,中美药典含量均匀度检查法的参数均可进一步优化,从而提高检查准确率。结论 中美药典含量均匀度检查法的准确率基本一致,提出了优化含量均匀度检查参数的新思路。     

Weighted Markov chains for forecasting and analysis Incidence of infectious diseases in jiangsu Province,China

This paper first applies the sequential cluster method to set up the classification standard of infectious disease incidence state based on the fact that there are many uncertainty characteristics in the incidence course.Then the paper presents a weighted Markov chain,a method which is used to predict the future incidence state.This method assumes the standardized self-coefficients as weights based on the special characteristics of infectious disease incidence being a dependent stochastic variable.It also analyzes the characteristics of infectious diseases incidence via the Markov chain Monte Carlo method to make the long-term benefit of decision optimal.Our method is successfully validated using existing incidents data of infectious diseases in Jiangsu Province.In summation,this paper proposes ways to improve the accuracy of the weighted Markov chain,specifically in the field of infection epidemiology.     

卡尔曼滤波在盾构姿态测量中的应用

三点法是一种传统的实时计算刚体三姿态角（滚动角、俯仰角和水平角）的方法。在盾构掘进过程中,观测点测量不同步会导致较大的姿态测量误差。采用卡尔曼滤波对观测点的坐标进行预测补偿来提高测量精度。建立系统运动的状态方程和量测方程,对系统噪声和量测噪声的协方差进行估计,通过递归运算对观测点坐标进行预测,蒙特卡洛仿真结果表明,这种处理方式优于传统三点法测量效果。仿真实验和测量实验结果都表明卡尔曼滤波算法既可以明显减小姿态角测量误差,又对随机系统噪声和量测噪声引起的姿态角误差具有抑制作用。     

HIV viral dynamic models with dropouts and missing covariates

In recent years HIV viral dynamic models have received great attention in AIDS studies. Often, subjects in these studies may drop out for various reasons such as drug intolerance or drug resistance, and covariates may also contain missing data. Statistical analyses ignoring informative dropouts and missing covariates may lead to misleading results. We consider appropriate methods for HIV viral dynamic models with informative dropouts and missing covariates and evaluate these methods via simulations. A real data set is analysed, and the results show that the initial viral decay rate, which may reflect the efficacy of the anti-HIV treatment, may be over-estimated if dropout patients are ignored. We also find that the current or immediate previous viral load values may be most predictive for patients' dropout. These results may be important for HIV/AIDS studies.     

广东省社区美沙酮维持治疗的评价与决策分析

目的通过Markov模型进行MonteCarlo模拟,对广东省社区美沙酮维持治疗进行评价与决策分析。方法建立Markov决策模型,应用MonteCarlo模拟进行成本效用分析。结果平均每个吸毒者30年中不维持治疗与维持治疗的费用分别为114.4(101.2～129.6)万元与81.9(62.4～102.3)万元,效用值分别为9.7(8.9～10.7)QALY与12.3(10.4～14.2)QALY,C/E分别为11.8(10.3～13.0)万元/QALY与6.7(4.5～9.6)万元/QALY,ICUR为-12.5万元/QALY。结论MonteCarlo试验模拟能估计成本与效用的变异,并能进行统计学检验,对于结果的预测有积极意义。