肿瘤药物临床试验中成组序贯设计的统计学考虑

成组序贯设计因其拥有较少的病例样本数和较早终止试验的可能性成为肿瘤药物临床试验设计方法的较好选择。如何科学有效地设计和应用成组序贯设计,本文通过Monte Carlo试验模拟,探讨肿瘤药物临床试验中成组序贯设计的期中分析次数、实施时间以及α消耗函数选取等问题,为读者系统指明如何去规划一次成组序贯试验以及如何确定其最优的试验参数。模拟结果表明,成组序贯设计以时间点2∶1∶1折半划分的三次期中分析为好,其期望样本含量仅为420.53。Lan-Demets的五种α消耗函数中,1.5次幂和2次幂的α消耗函数拥有最小期望样本含量约393例,相对于O＇Brien-Fleming设计和Po-cock设计在整体上更显优势。     

Interim analyses and sequential designs in phase III studies

Recruitment of patients to a clinical trial usually occurs over a period of time, resulting in the steady accumulation of data throughout the trial's duration. Yet, according to traditional statistical methods, the sample size of the trial should be determined in advance, and data collected on all subjects before analysis proceeds. For ethical and economic reasons, the technique of sequential testing has been developed to enable the examination of data at a series of interim analyses. The aim is to stop recruitment to the study as soon as there is sufficient evidence to reach a firm conclusion. In this paper we present the advantages and disadvantages of conducting interim analyses in phase III clinical trials, together with the key steps to enable the successful implementation of sequential methods in this setting. Examples are given of completed trials, which have been carried out sequentially, and references to relevant literature and software are provided.     

On adaptive error spending approach for group sequential trials with random information levels

A group sequential analysis following the error spending approach of Lan and DeMets ( 1983 ) requires that the maximum information level be fixed in advance. In practice, however, the maximum information level is often random, making it impossible to determine the information fractions required by Lan and DeMets ( 1983 ) to calculate the sequential boundary. We propose an adaptive error spending approach that further expands practical applications to settings where the interim information levels can depend on blinded accumulating data. We use a simple weighting method to combine independent test statistics from different stages, which are then compared with adaptive boundary values for the group sequential test. We develop a measure-theoretic framework and show that the adaptive error spending approach controls the type 1 error rates. Methods for point estimates and confidence intervals are also proposed. We warn that an error spending approach can lead to serious inflation of the type 1 error rates when the number or timing of interim analyses is allowed to depend on unblinded accumulating data.     

A Testing Strategy With Adaptive Dose Selection and Two Endpoints

The article deals with the design of a complex clinical trial with multiple doses of an experimental treatment tested against a control treatment, interim analyses and several endpoints characterizing treatment success. The closed test principle, methods from group sequential testing, and combination test methodology are combined to control the familywise error rate (FWER) when testing for treatment benefit. We also discuss strategies for utilizing the correlations between some of the relevant test statistics.     

Ⅰ期临床试验设计和需要重视的问题

Ⅰ期临床试验,特别是首次人类药物试验(First in human,FIH)具有极大的挑战性.在国外,试验设计方面近年来取得了很大进展.本文就Ⅰ期临床试验设计的技术、首剂量、安慰剂对照、剂量推升方案、终止标准和风险评估进行探讨.     

Optimal Timing for Interim Analyses in Clinical Trials

In clinical trials, interim analyses are often performed before the completion of the trial. The intention is to possibly terminate the trial early or adjust the sample size. The time of conducting an interim analysis affects the probability of the early termination and the number of subjects enrolled until the interim analysis. This influences the expected total number of subjects. In this study, we examine the optimal time for conducting interim analyses with a view to minimizing the expected total sample size. It is found that regardless of the effect size, the optimal time of one interim analysis for the early termination is approximately two-thirds of the planned observations for the O'Brien–Fleming type of spending function and approximately half of the planned observations for the Pocock type when the subject enrollment is halted for the interim analysis. When the subject enrollment is continuous throughout the trial, the optimal time for the interim analysis varies according to the follow-up duration. We also consider the time for one interim analysis including the sample size adjustment in terms of minimizing the expected total sample size.     

临床试验中平行组设计二分类指标样本量的计算

临床试验中所需病例数应符合统计学要求,以确保对所提出的问题给予可靠的回答。样本的大小通常以试验的主要指标来确定,同时应考虑试验设计类型、比较类型等。针对优效/非劣效/等效性试验的目的及统计假设检验和方差,文中介绍了二分类指标平行组试验设计样本量的计算方法和通用公式,并结合临床试验的实际案例对样本量计算进行了应用分析。     

新型冠状病毒肺炎药物干预型临床试验统计与分析

目的 通过对新型冠状病毒肺炎药物干预型临床试验进行统计和分析,对相关试验药物研究基础进行归纳和总结,为临床试验的注册和开展提供参考。方法 以中国临床试验注册中心和美国临床试验注册中心数据库为数据来源,结合国内外文献调研,对药物干预型试验的注册时间、研究类型与设计、纳入标准、样本量、研究实施地点、主要评价指标、特殊人群试验进行统计分析,并对相关药物在抗病毒、呼吸系统疾病等方面的研究进行总结。结果 截至2020年3月5日,共注册350项临床试验,其中药物干预型研究199项,其中化学药物干预占比30%,中药干预占比23%,生物制品干预占比25%,联合用药干预占比9%;随机平行对照试验占75%;涉及药物包括蛋白酶抑制剂、广谱抗病毒药物、对症治疗药物、中成药及生物制剂。结论 目前临床试验注册数量较多,有利于较快筛选出有效的临床用药,但应重点关注临床试验的伦理审查,并采取有效的措施确保临床试验科学有序的开展,促进将临床试验和临床救治的密切结合。     

ON THE TIMING OF A FUTILITY ANALYSIS IN CLINICAL TRIALS

In recent years, many researchers have been interested in performing futility analyses at interim points during clinical trials in order to terminate futile trials. To implement such an analysis, the researcher must decide what percentage of the total number of patients must have completed the trial before the interim analysis is done. This percentage is usually between 20% and 80%. We examined the relationship between the percentage chosen and the probability of stopping the trial, given a parameter value associated with the treatment effect. The results of this examination will help the researcher plan when to do a futility analysis.     

Multistage Designs for Vaccine Safety Studies

In a placebo-controlled vaccine safety trial, the primary interest is to demonstrate that the vaccine is sufficiently safe, rejecting the null hypothesis that the relative risk of an adverse event attributable to the vaccine is above a prespecified value, greater than one. We develop sequential as well as multistage designs for such trials where the interim analyses are conducted not after a given number of subjects but rather after a given number of events observed. We show that these designs achieve significant improvement over single-stage conditional test in terms of both the required number of events to be observed and the required number of subjects to be enrolled.     

Multistage designs for vaccine safety studies

In a placebo-controlled vaccine safety trial, the primary interest is to demonstrate that the vaccine is sufficiently safe, rejecting the null hypothesis that the relative risk of an adverse event attributable to the vaccine is above a prespecified value, greater than one. We develop sequential as well as multistage designs for such trials where the interim analyses are conducted not after a given number of subjects but rather after a given number of events observed. We show that these designs achieve significant improvement over single-stage conditional test in terms of both the required number of events to be observed and the required number of subjects to be enrolled.     

新药临床试验的中间分析和成组序贯试验

出于对目前新药临床试验的形势要求 ,使试验在技术上能与国际协调会议 (ICH)与GCP相衔接。本文介绍新药临床试验的中间分析和成组序贯试验。应用该方法一般能节约病例数 2 0 %以上 ,因此也节约了时间与费用。本文应用较浅近的方法介绍如何使用中间分析及用绘图法使用成组序贯试验 ,并介绍与固定样本试验法的比较 ,从而使读者能了解其优越性以使在新药临床试验中有较大的获益。     

我国儿科药物临床试验数据分析及启示

目的:研究我国儿科药物临床试验登记现状,为促进儿科药品研发提供建议与参考.方法:收集国家药品监督管理局药品审评中心(CDE)药物临床试验登记与信息公示平台中儿科药物公示信息,对试验类型、试验分期、受试者招募、保险、临床试验数据监察委员会(DMC)等信息采用比率法进行统计分析.结果与结论:截至2020年6月份,平台共登记...     

简单介绍成组序贯设计在临床试验中的应用

在临床试验中，常常因为伦理或经济的原因需要进行期中分析，成组序贯设计是ICH-GCP推荐的期中分析方法。本文对该方法的原理及其在临床试验中的几个问题：期中分析的次数、检验界值、样本估算和终点指标的影响等进行了简单介绍。     

Statistical Considerations for Testing Multiple Endpoints in Group Sequential or Adaptive Clinical Trials

Many clinical trials are designed with a fixed sample size or total number of events to detect a postulated size of treatment effect on a primary efficacy endpoint. When the trial is completed and the primary efficacy endpoint achieves statistical significance, formal statistical testing of other clinically important secondary endpoints often follows in order for the statistically and clinically significant results of these endpoints to be included in the label of the test pharmaceutical product. In conventional fixed designs without any interim analysis or trial extension, these endpoints are often tested in a pre-specified hierarchical order, following the closed testing principle. This testing strategy ensures a strong control of the overall type I error. However, when trials are conducted using a group-sequential design with interim analyses or can be extended using an adaptive design with an increase of sample size or total number of events, this conventional hierarchical testing strategy may violate the closure principle and the overall type I error rate may not be controlled in the strong sense.     

Statistical considerations for testing multiple endpoints in group sequential or adaptive clinical trials

Many clinical trials are designed with a fixed sample size or total number of events to detect a postulated size of treatment effect on a primary efficacy endpoint. When the trial is completed and the primary efficacy endpoint achieves statistical significance, formal statistical testing of other clinically important secondary endpoints often follows in order for the statistically and clinically significant results of these endpoints to be included in the label of the test pharmaceutical product. In conventional fixed designs without any interim analysis or trial extension, these endpoints are often tested in a pre-specified hierarchical order, following the closed testing principle. This testing strategy ensures a strong control of the overall type I error. However, when trials are conducted using a group-sequential design with interim analyses or can be extended using an adaptive design with an increase of sample size or total number of events, this conventional hierarchical testing strategy may violate the closure principle and the overall type I error rate may not be controlled in the strong sense.     

Consistently Modest Antidepressant Effects in Clinical Trials: the Role of Regulatory Requirements

Despite being widely heralded following their discovery, the effectiveness and clinical utility of antidepressants has been questioned, in part due to the release of several decades of regulatory trial data. Upon investigation, contemporary regulatory trials of antidepressants have demonstrated a nearly identical effect size (0.3) for the past 40 years, regardless of placebo response or attempts to improve trial design.In this review, we examine the historical methods of antidepressant trials and re-evaluate regulatory trial data over time and according to drug class (SSRIs, SNRIs, and atypicals) with the addition of two classes of antidepressants not previously analyzed: tricyclics used as active comparators and the recently-approved NMDA receptor antagonist, esketamine. We show that among these five classes of antidepressants there were no significant differences between effect sizes or percent symptom reduction. We suggest that within the context of a regulatory trial of antidepressants, effect sizes will remain modest (~0.3) regardless of class or novel drug mechanism, possibly due to regulatory changes to trial design and conduct following the Kefauver-Harris Act of 1962. We comment that the regulatory double-blind, parallel, placebo-controlled trial model is an artificial creation for a narrow purpose—designed to demonstrate simple superiority over placebo and to determine basic safety. We should be cautious of stretching trial results beyond their limited capacity to inform clinical practice as trials are not representative of real-world patients or medication management practices. There is a substantial need to develop more realistic models to evaluate the clinical utility of antidepressants.     

Mixture-based gatekeeping procedures in adaptive clinical trials

ABSTRACT

Clinical trials with data-driven decision rules often pursue multiple clinical objectives such as the evaluation of several endpoints or several doses of an experimental treatment. These complex analysis strategies give rise to “multivariate” multiplicity problems with several components or sources of multiplicity. A general framework for defining gatekeeping procedures in clinical trials with adaptive multistage designs is proposed in this paper. The mixture method is applied to build a gatekeeping procedure at each stage and inferences at each decision point (interim or final analysis) are performed using the combination function approach. An advantage of utilizing the mixture method is that it enables powerful gatekeeping procedures applicable to a broad class of settings with complex logical relationships among the hypotheses of interest. Further, the combination function approach supports flexible data-driven decisions such as a decision to increase the sample size or remove a treatment arm. The paper concludes with a clinical trial example that illustrates the methodology by applying it to develop an adaptive two-stage design with a mixture-based gatekeeping procedure.     

随机对照试验设计及实践心得

随机对照临床试验是医学研究最重要的研究类型之一，科学的设计和规范的实施是保证研究结果真实、可靠的重要前提。作者结合临床试验方案设计的准则及实践心得，对开展随机对照临床试验的研究终点、样本量估算、随机化和分配隐藏、盲法、分析集、中期分析、在线注册、数据管理、研究报告撰写等关键环节进行了简明的总结，以期为临床试验项目的开展提供参考。     

亚抗菌剂量多西环素治疗牙周炎的临床评价

目的：评价亚抗菌剂量多西环素（subantimicrobial dose doxycycline,SDD）在牙周炎治疗中的安全性和有效性.方法：对文献报告的SDD用于牙周炎临床治疗的多个大型、多中心、安慰剂对照试验结果进行分析总结.结果：在刮治＋根面平整术的基础上再给予SDD治疗牙周炎,能有效提高牙周组织的临床附着水平,降低探诊深度,改善牙周袋内位点数目,且不良反应发生率低,也不易产生细菌耐药性.结论：SDD是牙周炎临床治疗中安全有效的给药方法.