Performance characteristics of the adjusted r2 algorithm for determining the start of the terminal disposition phase and comparison with a simple r2 algorithm and a visual inspection method

The adjusted r² algorithm is a popular automated method for selecting the start time of the terminal disposition phase (t_z) when conducting a noncompartmental pharmacokinetic data analysis. Using simulated data, the performance of the algorithm was assessed in relation to the ratio of the slopes of the preterminal and terminal disposition phases, the point of intercept of the terminal disposition phase with the preterminal disposition phase, the length of the terminal disposition phase captured in the concentration‐time profile, the number of data points present in the terminal disposition phase, and the level of variability in concentration measurement. The adjusted r² algorithm was unable to identify t_z accurately when there were more than three data points present in a profile's terminal disposition phase. The terminal disposition phase rate constant (λ_z) calculated based on the value of t_z selected by the algorithm had a positive bias in all simulation data conditions. Tolerable levels of bias (median bias less than 5%) were achieved under conditions of low measurement variability. When measurement variability was high, tolerable levels of bias were attained only when the terminal phase time span was 4 multiples of t_1/2 or longer. A comparison of the performance of the adjusted r² algorithm, a simple r² algorithm, and t_z selection by visual inspection was conducted using a subset of the simulation data. In the comparison, the simple r² algorithm performed as well as the adjusted r² algorithm and the visual inspection method outperformed both algorithms. Recommendations concerning the use of the various t_z selection methods are presented.     

相变的分类及其特征

本文以吉布斯自由能的偏微商作为相变分类的依据,为相变特征指明了理论根据．并给出了示例．     

一个不可逆相变问题解的先验估计

给出了一个不可逆相变问题,证明了给定ｓ（ｔ）时其解的先验估计．     

SPIRIT: A seamless phase I/II randomized design for immunotherapy trials

Immunotherapy—treatments that enlist the immune system to battle tumors—has received widespread attention in cancer research. Due to its unique features and mechanisms for treating cancer, immunotherapy requires novel clinical trial designs. We propose a Bayesian seamless phase I/II randomized design for immunotherapy trials (SPIRIT) to find the optimal biological dose (OBD) defined in terms of the restricted mean survival time. We jointly model progression‐free survival and the immune response. Progression‐free survival is used as the primary endpoint to determine the OBD, and the immune response is used as an ancillary endpoint to quickly screen out futile doses. Toxicity is monitored throughout the trial. The design consists of two seamlessly connected stages. The first stage identifies a set of safe doses. The second stage adaptively randomizes patients to the safe doses identified and uses their progression‐free survival and immune response to find the OBD. The simulation study shows that the SPIRIT has desirable operating characteristics and outperforms the conventional design.     

Patient-specific dose finding in phase I clinical trials

This article proposes an extension of the continual reassessment method to determine the maximum tolerated dose (MTD) in the presence of patients' heterogeneity in phase I clinical trials. To start with a simple case, we consider the covariate as a binary variable representing two groups of patients. A logistic regression model is used to establish the dose–response relationship and the design is based on the Bayesian framework. Simulation studies for six plausible dose–response scenarios show that the proposed design is likely to determine the MTD more accurately than the design that does not take covariate into consideration.     

Monitoring of autocorrelated general linear profiles

A collection of quality data represented by a functional relationship between response and explanatory variables is called a profile. In the literature, the errors of profiles are often assumed to be independent. However, quality data often exhibits time correlations in real applications. Therefore, in this paper, we investigate a general linear regression model with a between-profile autocorrelation. We propose a multivariate exponentially weighted moving average chart for monitoring shifts in the regression parameters, and an exponentially weighted moving average chart for monitoring shifts in the standard deviation. A simulation study reveals that our proposed schemes outperform competing existing schemes based on the average run length criterion. An example is used to illustrate the applicability of the proposed scheme.     

Adaptive designs for selecting drug combinations based on efficacy–toxicity response

We propose a new adaptive procedure for dose-finding in clinical trials with combination of two drugs when both efficacy and toxicity responses are available. We model the distribution of this bivariate binary endpoint using the bivariate probit model. The analytic formulae for the Fisher information matrix are obtained, that form the basis for derivation of the locally optimal, minimax, Bayesian, and adaptive designs in the framework of optimal design theory.     

测定光纤折射率的简易方法

本文利用光导纤维中光速的测定原理,采用一种方波调制信号,应用具有异或逻辑功能的门电路进行相差测量的巧妙方法得到光在光导纤维中的传输速度,再利用,从而快速测得光纤的折射率[1]。     

北三台凸起石炭系火山岩地震响应及分布规律

火山岩是北三台凸起石炭系主要储集层，从下向上可划分出3个火山序列，利用合成地震记录标定技术可建立井下火山岩相与井旁地震响应特征之间的对应关系，借助三维地震资料对各个火山序列界面进行地震对比解释，然后对每个火山序列进行地震相划分，共识别出5种主要地震相。根据单井相标定关系可将地震相转换为火山岩相，从而再现了研究区石炭系火山岩相的分布特征。综合石炭系顶部遭受剥蚀程度、断裂发育、火山岩岩相分布特征、石炭系上覆盖层发育程度、井下油气显示情况和与生烃凹陷的距离等因素，确定出北三台凸起石炭系火山岩油气勘探有利区带。     

分相势垒的热力学分析

从热力学角度分析了分相过程中存在的势垒及其影响因素。