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1.
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.  相似文献   

2.
目的针对医学研究中常见的定量资料等效性检验、非劣效性检验存在的问题,探讨应用线性回归模型理论进行定量资料的等效性检验、非劣效性检验,并给予统计软件技术上的支持。方法从线性回归模型的构造出发,根据模型中参数的统计学意义,结合等效性检验、非劣效性检验原理,利用SAS统计软件包,结合实例,编写程序,并计算相应的统计量。结果分别对平行设计和多中心设计的定量资料进行统计学检验,并对主要输出结果进行了解释。结论探索出在临床研究中利用线性回归模型,通过SAS软件包进行统计学检验的途径,并为类似问题的解决提供了理论参考。  相似文献   

3.
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,…  相似文献   

4.
目的介绍临床试验期中分析时条件把握度的计算原理及样本含量再估计方法。方法根据信息时间,构造B统计量,运用布朗运动理论,估计条件把握度,并据此采用二分搜索法估计后一阶段所需样本含量。以正态分布资料为例,介绍计算过程。结果如果试验期初对参数的估计不准确,可以根据试验中期数据,计算条件把握度。如果条件把握度较低,则通过调整样本含量可以达到期望把握度;如果条件把握度较高,则可以提前结束临床试验。结论该方法可以在试验过程中有效监测检验效能,在不违背临床试验方案的前提下,通过调整样本含量,保证临床试验达到预期的检验效能。  相似文献   

5.
样本量估计是研究设计中的一个极为重要环节,如何正确估计样本量即使对于统计专业人员都是较难把握的技能.目前,无论是统计专业人员还是非专业人员在实施样本量估计时大多面临以下三个问题:其一,目前国内尚缺乏系统地介绍样本量估计方法的文献,从而导致在实验设计阶段进行样本量估计时手段受限,尤其涉及到临床试验中应用较多的非劣性检验和等效性检验,以及一般研究中非参数检验、多元回归和相关分析的样本量估计方法.其二,由于国内的教科书、专著和一些相关的期刊论著在介绍样本量估计方法时缺乏源头文献的引用,加之某些设计的样本量估计方法不止一种,我们采用的方法是否准确和权威?  相似文献   

6.
长久以来,国内一直缺乏系统介绍样本量估计的专著或文献,当涉及到较复杂的样本量估计方法时,如多因素、多变量、非参数方法的样本量估计,以及等效性或非劣性的样本量估计,如何依据权威文献并予以实施,即使对专业人员也是一种挑战。针对这一现状,陈平雁教授带领的南方医科大学生物统计学本科生团队,以目前国际上公认的样本量估计权威软件nQuery Advisor7.0为蓝本,系统地介绍了样本量估计方法及其权威出处,同时公开无偿地给出了SAS程序供读者应用,这为专业人员借助我刊引用源头文献无疑提供了极大便利,同时也为这一领域的研究起到了很好的引导作用。从本期开始,我刊将连载陈平雁团队关于样本量估计的系列文章。正如作者所言,样本量估计的方法较多,这里介绍的方法未必是最好的,甚至也有可能不完全正确或出现疏漏,我们希望读者能够及时指出问题,如果有不同看法,我们会积极支持在我刊展开针对性讨论,以求去伪存真。  相似文献   

7.
校正中心效应的非劣性检验   总被引:1,自引:1,他引:0  
目的解决校正中心效应的非劣性检验的问题。方法借助多重回归中的回归系数及其标准误表达式,试图得到校正中心效应的非劣性检验统计量。结果导出校正中心效应的非劣性检验的方法,并且可以借助多重回归校正中心效应的部分结果进行非劣性检验。并用实例说明了具体的计算步骤。结论可以用本文所介绍统计方法进行校正中心效应的非劣性检验。  相似文献   

8.
目的比较6种不同的平均生物等效性试验的设计方法的检验效能与所需的样本含量.方法采用Monte-Carlo方法,对不同参数组合下,6种设计方法的检验效能或样本含量进行模拟.结果 6种平均生物等效性评价试验的设计方法中,以4×4交叉设计的效率最高,而平行组设计和Balaam设计的效率较低.在相同参数组合下,所需的样本含量由少到多的顺序为:4×4交叉设计、2×4交叉设计、2×3交叉设计、2×2交叉设计、平行组设计和Balaam设计.结论对于平均生物等效性而言,采用4×4交叉设计或2 × 4交叉设计效果较好.  相似文献   

9.
非劣效性和等效性随机对照试验的应用日益广泛,为医疗卫生干预提供了重要的证据。对其结果的准确评价有赖于充分、准确的报告。CONSORT声明向非劣效性和等效性随机对照试验的扩展是2006年提出的又一个报告规范。本文介绍非劣效性和等效性随机对照试验的特殊方法学问题、实施与报告现状以及CONSORT扩展声明的清单,并对清单中的部分条目进行了解释与说明。  相似文献   

10.
[目的]探讨在双正态假定下,应用标准化差法在Bootstrap再抽样基础上利用SAS软件包编程进行定量资料ROC曲线下面积的估计及其非劣效性检验,以比较两氧化低密度脂蛋白试剂盒在冠心病诊断中的价值。[方法]从ROC曲线的定义出发,通过编写SAS宏程序完成ROC曲线下面积的估计,在Bootstrap基础上获得标准误的估计值,从而根据非劣效性检验原理进行参数检验,或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。  相似文献   

11.
OBJECTIVE: To present and compare three statistical approaches for analyzing a noninferiority trial when the noninferiority margin depends on the control event rate. STUDY DESIGN AND SETTING: In noninferiority trials with a binary outcome, the noninferiority margin is often defined as a fixed delta, the largest clinically acceptable difference in event rates between treatment groups. An alternative and more flexible approach is to allow delta to vary according to the true event rate in the control group. The appropriate statistical method for evaluating noninferiority with a variable noninferiority margin is not apparent. Three statistical approaches are proposed and compared: an observed event rate (OER) approach based on equating the true control rate to the observed rate, a Bayesian approach, and a likelihood ratio test. RESULTS AND CONCLUSIONS: Simulations studies indicate that the proportion of trials in which noninferiority was erroneously demonstrated was higher for the OER approach than with the Bayesian and likelihood ratio approaches. In some cases, the Type I error rate exceeded 10% for the OER approach. The OER approach is not recommended for the analysis of noninferiority trials with a variable margin of equivalence. The Bayesian and likelihood ratio methods yielded better operating characteristics.  相似文献   

12.
Clinical trials now often involve thousands of patients, and statisticians emphasize the importance of trial size in ensuring that 'correct' answers are obtained. However, when a good treatment appears for a disease that was hitherto untreatable - for example, oranges for scurvy or streptomycin for tuberculosis - only a small trial is needed. Large trials are only needed to demonstrate small effects. The meta-analysis of small trials is often misleading, and may hide undesirable effects of individual drugs. The concept of equivalence between treatments is important, and while a statistically adequate equivalence trial may have to be very large, many clinicians will question the need for extreme statistical propriety. Clinical trials often do not reflect 'real world' practice, and the clinical relevance of a trial is more important than its size.  相似文献   

13.
Background. – The existence of effective reference treatments means that the superior therapeutic efficacy of new treatments is less marked and thus more difficult to demonstrate statistically. Moreover, the potential value of a new treatment is also based on other criteria, such as costs, ease of use, non invasiveness, and immediate or long-term side effects. In this context, methodological issue becomes one of looking for equivalence or non inferiority of the new treatment in comparison with an existing, high-performance reference treatment.Methods. – In the present work, we reexamine the statistical rational and methodological features of equivalence and noninferiority trials.Results. – We address equivalence margin choice, hypotheses building, and the different approaches for establishing equivalence (hypothesis testing and confidence intervals). We then discuss key aspects of equivalence trial design and the important methodological quality criteria involved in performing such studies: choice of the reference treatment, subject eligibility criteria, primary endpoint, study population and the required sample size. Lastly, we consider the possibility of adopting a new analytical strategy (noninferiority/superiority).Conclusion. – A checklist of items to include when reporting the results of randomized controlled trials (Consolidated Standards of Reporting Trials, the CONSORT recommendations) has been adapted for use in noninferiority and equivalence randomized controlled trials.  相似文献   

14.
目的:为科学设计医疗器械的临床试验,合理选择试验样本含量。方法:利用统计方法对医疗器械临床试验的样本含量计算进行探讨,并结合一些案例进行分析。结果:提供了常用统计参数的样本含量查询表,所提出的计算方法经验证方便可行。结论:医疗器械临床试验样本含量可通过查询表方式快捷获取。  相似文献   

15.
An equivalence trial is appropriate when it is desired to demonstrate equivalence between two treatments, regimens or interventions (methods) or non-inferiority of a new one compared to a standard one. The conduct of an equivalence trial requires different techniques during design and analysis compared to a superiority trial. The existing formulae for sample size calculation to demonstrate equivalence between two methods using the confidence interval approach are reviewed. The establishment of the margin of equivalence and the choice of the type of test are discussed. Plots of sample sizes required to demonstrate equivalence in the case of binary outcomes are presented for values of proportions and margins of equivalence common in the reproductive health field. Examples are given of method comparisons in the reproductive health field in which the relevant question is to demonstrate non-inferiority. The approach to equivalence is described in the trials included in three published systematic reviews in which these comparisons were conducted, addressing the statement of hypotheses, sample size calculation and the interpretation of results. The use of the conventional superiority approach to design equivalence trials has led to underpowered trials to show equivalence within clinical relevant margins. The analysis and interpretation of results from such trials has resulted in conclusions of equivalence based on lack of significance. We draw attention to the lack of awareness of the appropriate techniques for equivalence trials among researchers in the field of reproductive health. Finally, the issue of interim analyses and stopping rules in equivalence trials is addressed.  相似文献   

16.
Trials for demonstrating the ‘equivalence’ of active standard and test treatments generally require large sample sizes that depend on the definition of ‘equivalence’ and the overall event rate when the outcome is incidence of an event such as morality. The planning of sample sizes for such trials requires specification of a value for the overall event rate. This value often will reflect the outcomes of previous trials of the standard treatment, and is subject to uncertainty that needs some accommodation, to protect against an inadequate sample. Bayes and Empirical Bayes methods can be used to incorporate information from one or more previous trials into the sample size calculation when equivalence means high confidence that the event rate ratio is less than some specified value.  相似文献   

17.
A controlled single subject trial compares the efficacy of a new treatment with a control treatment in an individual patient. The treatments are administered in a double-blind, randomized, multi-crossover sequence of periods. During the trial response measures are obtained from each treatment period and form the basis for the statistical evaluation. Similar to the situation in clinical trials using groups of patients the statistical power is dependent on sample size, variability of responses, magnitude of the differential treatment effect and the level of statistical significance. In addition, the randomization procedure is of importance and power estimations show that a pairwise random allocation of treatment periods is more powerful than an unrestricted randomization. Since a single subject trial is a time consuming approach, the total number of treatment periods, the sample size, is restricted in order to make such trials feasible. Accordingly, less rigorous statistical requirements and power must be accepted. The consequence is an increased risk of both Type I and II errors. However, in comparison with the trial and error approach frequently applied in clinical practice, the controlled single subject trial may improve the certainty of therapeutic decisions in the individual patient.  相似文献   

18.
随机模拟法验证非劣效临床试验样本量计算公式   总被引:4,自引:0,他引:4  
目的探讨并验证非劣效临床试验样本量计算方法。方法通过理论公式的推导,得到非劣效临床试验样本量计算公式,并用随机模拟的方法,使用该公式计算出的样本量估计实际的检验效能,以验证公式的正确性。结果由概率论严格推导得到样本量计算公式,并通过SAS随机模拟宏程序验证了公式的正确性,即模拟出的检验效能与最初带入公式计算时设定的预期的检验效能一致。结论样本量计算与临床试验设计有机结合的方法,解决了现行临床试验样本量计算方法与研究设计脱节的问题。  相似文献   

19.
In trials of physical and talking therapies, nesting of patients within therapists has statistical implications analogous to those of cluster randomised trials. Nevertheless, the clustering effect may be more complex, as it interacts with treatment. For some therapies, individual patients may receive care from multiple therapists of the same type, so that patients are no longer strictly nested within therapists, creating a ‘multiple‐membership’ relationship between patients and therapists. This paper considers methods of analysis and sample size estimation for trials with multiple‐membership clustering effects. It is motivated by a trial of a psychotherapy for the treatment of adolescent depression with cognitive behavioural therapy. We tested methods and issues in a Monte Carlo simulation study, simulating trials with multiple membership. Results demonstrate satisfactory performance in terms of convergence and give estimates of the intra‐cluster correlation coefficient and empirical test size similar to a simple hierarchical design. We derive formulae for sample size and power for multiple‐membership trial designs. We then compare estimates of power from this formula with empirical power derived from the simulation study. Finally, we show that we can easily extend formulae for sample size and power to allow consideration of power and sample size for certain types of more complex interventions. These include situations where therapists of different types deliver separate components of the intervention, creating a cross‐classified relationship, or where several therapists deliver a group‐administered treatment, creating further levels. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   

20.
There are different kinds of randomised controlled trials: trials in which the superiority of a treatment can be demonstrated (superiority trials) and trials in which the equal efficacy of two treatments can be shown (equivalence trials). The main reason for performing an equivalence trial is that for many diseases and disorders an effective treatment already exists. Equivalence trials are appropriate when a new treatment offers some advantages over an existing treatment (less cost, greater safety, improved convenience or freedom of choice for the patient), in addition to the expected equal therapeutic effectiveness. The design of equivalence trials is to a large extent comparable to that of superiority trials, but there are some methodological differences. In equivalence trials, the null hypothesis and alternative hypothesis are interchanged, compared to superiority trials. In equivalence trials, an equivalence margin is defined for the different treatments. Clinical professionals decide on the equivalence margin beforehand on the basis of the clinical relevance. To demonstrate equivalence, the confidence interval of the difference between two treatments must lie completely within the equivalence margin. In equivalence trials, there are usually more patients needed: the smaller the equivalence margin, the more patients are needed. In equivalence trials, both per-protocol analyses and intention-to-treat analyses should be used to prove the equal therapeutic effectiveness of the treatments under study.  相似文献   

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