三种不同方法估算等效性检验的样本量与检验效能

关于等效性检验的样本量与检验效能估计,SAS中提供了一种方法的估算程序,即Phillips法,但是只是针对于单样本、两样本与配对设计而言。然而,在以等效性检验为目的的临床试验中,双处理、两阶段交叉设计应用最为广泛,并在1992年被美国FDA定义为用于等效性评价的标准方法〔1,2〕。这种设计能提供药物间的差(或比)的最优无偏估计;节约样本,兼有既平行、又配对两种设计的优点。本研究将Phillips方法进一步推广到2×2交叉设计并与其他估算等效性检验样本量与检验效能的两种方法作了比较,以期为研究者提供参考。方法简介1.一般方法通常情况下,…     

等效性检验与差异性检验的区别及其模拟验证

目的说明等效性检验和传统差异性检验相同与不同之处,并为在一定条件下用差异性检验替代等效性检验的可能性提供线索。方法用计算机模拟的方法验证两种假设检验的关系。结果等效性检验和传统差异性检验有区别也有联系。结论在一定参数条件下,差异性检验结果为P>α时,可下等效结论。     

改良终点法和原终点法在临床生化检验中的作用

目的对临床生化检验中改良终点法和原终点法的作用进行对比分析。方法临床对两种检验方法进行使用,对比分析改良终点法和原终点法之间的相关性以及线性浓度。结果在检测结果差异对比中,两种方法差异不明显,不具有统计学意义（P〉0.05）;改良终点在正常浓度下的批内CV和总CV测定要高于原终点法,在异常情况下低于原终点法,两者之间差异显著,具有统计学意义（P〈0.05）;改良终点法在高浓度测量下其线性浓度测定范围要大于原终点法,两者之间差异显著,具有统计学意义（P〈0.05）。结论在生化高浓度检验中,改良终点法应用优势明显高于原终点法,因此可以对改良终点法进行推广使用。     

显著性检验与等效性检验的区别与联系

传统显著性检验(Significance eSt)用于推断样本所代表的总体均数是否相等，它的检验假设为样本来自同一总体(即总体均数相等)。在应用中，显著性检验结果不能评价差别的大小，也不能说明差别是否有实际意义，所谓差别显著，是指在统计学理论上认为样本来自不同的总体。     

模拟验证等效性检验中β的单、双侧取值

目的 研究临床试验中等效性检验的样本量的计算问题.方法 在概括总结影响等效性检验的样本量与检验效能的几个主要因素（α、β、θ、△、σ）的基础上,重点介绍了等效性检验中α与β的确定与含义,并指出了文献中所存在的分歧;然后利用计算机抽样模拟的方法,依据不同设计类型、不同参数取值下计算的样本量,模拟估算所对应的检验效能.结果 模拟验证了β应该取单侧还是双侧并给出了较为合理的解释.结论 在等效性检验的样本量估算中,当θ为0时,β取双侧;当θ不等于0时,β取单侧.     

临床试验中多终点期中分析方法研究

[目的]介绍临床试验中多终点期中分析方法。[方法]在多终点分析的基础上将单变量成组序贯期中分析方法进一步扩展,介绍多终点(变量)期中分析方法。[结果]多终点期中分析方法可以分为2大类,分别对每个终点进行单变量分析,同时对每个终点的检验界值进行校正;或利用所有观察终点构造总的检验统计量进行分析。[结论]确定单变量成组序贯期中分析界值的方法可以扩展用于多终点期中分析。     

药品检验中等效区间的确定方法与应用效果探讨

目的:探讨药品检验中等效区间的确定方法与应用效果.方法:采用容忍区间检测、参数法检测、非参数法检测、标准品与不合格品的界限检测方法来判断待验品与标准品是否等效.结果:在95％置信区间,单侧比例为76％的样本中容忍区间为(1.127,0.887),如检验样品置信区间在(1.127,0.887)范围内,则说明检测样品与标准...     

两冠心病诊断试剂盒双正态ROC曲线下面积及其等效性或非劣效性检验

目的 探讨在双正态假定下,应用标准化差法进行定量资料ROC曲线下面积的估计及其等效性检验或非劣效性检验,比较两氧化低密度脂蛋白试剂盒在诊断冠心病中的价值.方法 从ROC曲线的定义出发,根据模型中参数的统计学意义,完成ROC曲线的构建、曲线下面积的估计,并利用标准化差结合等效性检验、非劣效性检验原理,进行参数检验,或在Bootstrap基础上利用可信区间法得到结论.结果 两试剂盒均显示氧化低密度脂蛋白在冠心病诊断中具有较高的准确性.从非劣效性检验的结果可以看出,CHN试剂盒在冠心病诊断上非劣于已经投入临床使用的SWZ试剂盒.结论 两试剂盒具有较高的临床推广价值,且具有较高性价比的CHN试剂盒在国内临床市场有较好的前景.同时为类似问题的解决提供了方法学参考.     

基于非参数回归的生物等效性多重检验

目的本文提出一种基于非参数模型的生物等效性检验的新方法。方法首先利用非参数回归的方法估计血药浓度-时间曲线,并建立血药浓度估计值线性混合效应模型估计药物效应系数,在此模型的基础上采用多重检验的方法对曲线上每一时间点处的药物效应系数进行生物等效性检验。若在所有时间点处等效,则两种药物等效。结果模拟和实例分析表明此方法能消除周期效应和序列效应的影响,同时在数据稀疏时可降低生物等效性检验的I类误差率,并能提高在测量误差较大时的检验效能。结论本文提出的多重检验方法有较高的检验效能和较低的I类误差率,可应用于生物等效性检验。     

幽门螺杆菌临床检验方法探讨

目的:探讨幽门螺杆菌的临床检验方法.方法:选择本地区于2016年1月~12月期间感染幽门螺杆菌的100例患者为研究对象,回顾分析各个患者行嗜银染色法和快速尿素酶法检验的疗效.结果:采用嗜银染色法检验出33例患者,占比为33.00%;采用尿素酶法检验出42例患者,占比为42.00%;联合两种方法共检测出30例患者,占比达30.00%,两种检测结果各不相同的总共有15例患者,占比达15.00%.结论:通过在幽门螺杆菌感染患者行嗜银染色法和快速尿素酶法联合检验法,可以显著提升幽门螺杆菌的临床检验率,值得临床进行推广和应用.     

Meta分析中多变量多水平模型方法的探讨

为了探讨多变量多水平模型在Ｍｅｔａ 分析中的应用价值，根据Ｍｅｔａ 分析中具有两个“效应尺度”的数据，拟合双变量两水平模型，估计有关参数以及预测值。结果表明，在模型中可同时获得两个平均“效应尺度”及其相关系数的估计，以及其影响因素的估计。Ｍｅｔａ 分析中如果具有不止一个“效应尺度”，则多变量多水平模型可获得多个平均“效应尺度”的估计值及其可信区间，也可分析多个平均“效应尺度”估计值之间的相关关系，探讨有关因素对这一关系的影响     

Statistical analysis of a micromethod in an interlaboratory test

A micromethod developed by Meier (1996) was assessed in an interlaboratory test with 7 labs supplying duplicate measurements on 5 to 9 days. This paper aims at evaluating the reproducibility and the repeatability of the micromethod. The effective concentration of microbicidal substances to reduce the number of test organisms by a factor of 10(5) was estimated from raw data of the microtiter test by means of a nonlinear regression model. Inclusion criteria were defined for the model fit and the results were checked for plausibility and for outliers according to methods prescribed by ISO 5725 (International Standard, 1994). From the remaining data (about 85% of the total data) inter-laboratory and intralaboratory reproducibility as well as repeatability were computed. The paper sets an example of how to analyze such interlaboratory tests. For practical purposes a table shows confidence limits of the relative precision for a broad range of interlaboratory test designs. In addition, test designs are given which lead to statistically qualified decisions about acceptance or rejection of a claimed effective concentration of a microbicidal substance. The results clearly qualify the micromethod for practical application in testing microbicidal substances.     

Likelihood ratio and score tests to test the non‐inferiority (or equivalence) of the odds ratio in a crossover study with binary outcomes

We consider the non‐inferiority (or equivalence) test of the odds ratio (OR) in a crossover study with binary outcomes to evaluate the treatment effects of two drugs. To solve this problem, Lui and Chang (2011) proposed both an asymptotic method and a conditional method based on a random effects logit model. Kenward and Jones (1987) proposed a likelihood ratio test (LRT_M) based on a log linear model. These existing methods are all subject to model misspecification. In this paper, we propose a likelihood ratio test (LRT) and a score test that are independent of model specification. Monte Carlo simulation studies show that, in scenarios considered in this paper, both the LRT and the score test have higher power than the asymptotic and conditional methods for the non‐inferiority test; the LRT, score, and asymptotic methods have similar power, and they all have higher power than the conditional method for the equivalence test. When data can be well described by a log linear model, the LRT_M has the highest power among all the five methods (LRT_M, LRT, score, asymptotic, and conditional) for both non‐inferiority and equivalence tests. However, in scenarios for which a log linear model does not describe the data well, the LRT_M has the lowest power for the non‐inferiority test and has inflated type I error rates for the equivalence test. We provide an example from a clinical trial that illustrates our methods. Copyright © 2016 John Wiley & Sons, Ltd.     

A multivariate test for population bioequivalence

In this article, we propose a multivariate generalization of the criteria for testing univariate population bioequivalence. Recently, a number of approaches for testing multivariate equivalence have appeared in the literature. Most of them consider a multivariate equivalence region, which implies simultaneous comparison of means in each dimension. In contrast, our proposal combines a comparison of means and a comparison of variances into a single aggregate criterion, using the trace of the covariance matrix as a scalar measure of the total variability. We use a confidence interval approach to multivariate population bioequivalence testing, similar to the univariate case. Two versions of the modified large-sample confidence interval for the linearized multivariate criterion are constructed. In a simulation study, we evaluate the empirical coverage of these confidence intervals and rejection rates of the corresponding tests in finite samples. The proposed methodology is illustrated with an example of testing equivalence of the spray pattern of nasal sprays.     

Test for qualitative interaction in equivalence trials when the number of centres is large

We propose a generalized testing procedure to test for qualitative interaction in equivalence trails when the number of centres is large. The proposed testing procedure allows for an adaptable definition of qualitative interaction that can take into account the total number of centres. A tuning parameter k (k > or = 0) is introduced to quantify qualitative interaction. The testing procedure is proposed for equivalence trials with symmetric or asymmetric margins. In addition to the test procedure, we also provide explicit formulae for the power calculation. The proposed test is relatively easy to implement using any statistical software. Examples for detecting qualitative interaction are given to illustrate the method.     

A statistical assessment of clinical equivalence

An observed confidence distribution is proposed as a measure of strength of evidence for practically equivalent efficacies of two treatments. The concept is independent of prior opinions about relevant sizes of a difference in efficacy. It also avoids retrospective power calculations for trials with missed recruitment goals and allows combination of the confidence from independent experiments.     

Shared genomic segment analysis with equivalence testing

An important aspect of disease gene mapping is replication, that is, a putative finding in one group of individuals is confirmed in another set of individuals. As it can happen by chance that individuals share an estimated disease position, we developed a statistical approach to determine the p-value for multiple individuals or families to share a possibly small number of candidate susceptibility variants. Here, we focus on candidate variants for dominant traits that have been obtained by our previously developed heterozygosity analysis, and we are testing the sharing of candidate variants obtained for different individuals. Our approach allows for multiple pathogenic variants in a gene to contribute to disease, and for estimated disease variant positions to be imprecise. Statistically, the method developed here falls into the category of equivalence testing, where the classical null and alternative hypotheses of homogeneity and heterogeneity are reversed. The null hypothesis situation is created by permuting genomic locations of variants for one individual after another. We applied our methodology to the ALSPAC data set of 1,927 whole-genome sequenced individuals, where some individuals carry a pathogenic variant for the BRCA1 gene, but no two individuals carry the same variant. Our shared genomic segment analysis found significant evidence for BRCA1 pathogenic variants within ±5 kb of a given DNA variant.     

The effects of non-compliance on intent-to-treat analysis of equivalence trials

The standard approach for analysing a randomized clinical trial is based on intent-to-treat (ITT) where subjects are analysed according to their assigned treatment group regardless of actual adherence to the treatment protocol. For therapeutic equivalence trials, it is a common concern that an ITT analysis increases the chance of erroneously concluding equivalence. In this paper, we formally investigate the impact of non-compliance on an ITT analysis of equivalence trials with a binary outcome. We assume 'all-or-none' compliance and independence between compliance and the outcome. Our results indicate that non-compliance does not always make it easier to demonstrate equivalence. The direction and magnitude of changes in the type I error rate and power of the study depend on the patterns of non-compliance, event probabilities, the margin of equivalence and other factors.     

Stratified analysis of multivariate clinical data: application of a Mantel-Haenszel approach

Laboratory determinations on children aged 6 to 10 years obtained over a 5-year period are analysed by a method described in detail for differentiating between children from exposed and control areas of Seveso, Italy. In the analysis, stratification is employed to distinguish the separate days of laboratory measurement. The analyses permit the study of differences based on all variables simultaneously as well as on each variable separately. Results are obtained for each individual year and for longer intervals of 2 successive years, 3 successive years, 4 successive years, and all 5 years. The results and some statistical aspects of the analysis are discussed.