药物临床试验方法学（赠光盘）

知名专家倾力打造,临床试验实践必备参考书。 中国药学会理事长桑国卫、协和医院主任医师、北京大学第一医院教授联袂推荐。 本书全面阐述了药物临床试验管理和操作的方法细节,涉及各期、各类药物临床试验全过程的管理和设计细节,详尽阐述了临床试验项目的实际技术操作手段和核心程序,对操作规范要点和方法讲解透彻。     

扩大试验重组凝血第Ⅷ因子

西德拜耳公司的日本法人拜尔药品公司扩大用基因工程生产的凝血第Ⅷ因子的临床试验.该凝血因子是美国Genentech公司和拜尔公司共同开发的产品,由美国制造,在欧美和日本进行临床试验.日本的临床试验是1988年12月由奈良县立医科大学小儿科学教授福井弘在3名患者身上进行的.1989年东京医科大学临床病理学教授藤卷道男的2名患者参加,以后以18岁以上5名患者为中心继续试验.到今年增加了11个治疗试验的单     

我国影像临床试验注册情况及其对科研管理的启示

???? 目的 分析和探讨我国影像医学临床试验注册现状及存在的问题。方法 收集中国临床试验注册中心2008—2012年的临床试验注册数据,使用SPSS16.0软件进行统计分析,组间构成比比较采用Pearson χ²检验。结果 5年间我国影像医学临床试验注册数呈明显上升趋势。2011—2012年注册试验的影像手段构成与2008—2010年注册试验不同, P=0.037,MRI（从18.18%到32.73%）、CT（从9.09%到18.18%）试验所占比例明显升高。影像医学临床试验采用诊断试验设计的比例最高,占37.98%,明显高于平均水平3.45%,P<0.001。结论 我国影像临床试验的管理逐渐规范,临床试验的科学性和可信度随之提高。加强临床试验预注册、完善试验设计是提高影像医学试验管理水平的重要措施。     

韩国积极吸引海外临床试验0期临床试验能否成为热门货

韩国食品药品管理局（KFD）宣布,2011年上半年将制订0期临床试验（微剂量药物试验）的指南,以强化早期临床试验的体制。 据KFD透露,在韩国实施的临床试验中,0期和I期试验等早期临床试验每年约90例,以占临床试验总数20％的速度增长。如果仅限于0期试验,从2008～2010年上半年,被批准的试验每年仅有1个而已。     

寻找秃顶男子

Pro Cyte Corp.(Kitkland,WA)正在欧洲扩展其抗秃头药物Triccomin~TM的二期临床试验。迄今为此的前临床及临床试验均表明这种肽-铜药物可增加男性脱发症患者的毛发数量。目前,获准进入美国市场的治脱发药物只有Rogaine~Tm一种。Tricomin将是第二种。不过,道路还长得很。ProCyte还必须在美国进行前临床试验,更不用提还有三期临床试验等在前面。在欧洲进行的第二期临床试验将在第一季度结束。据公司称,接受涂抹治疗的24名患者中,80%出现良好的毛发生长状况。     

我国仿制药人体生物等效性临床试验研究室建设的现状与发展路径

我国开展仿制药一致性评价最主要的困难之一是临床试验资源不足,解决办法是考虑将生物等效性临床试验资格认定调整为备案 管理。因此,对备案的医疗机构建设生物等效性试验研究室是一个潜在的挑战。文章分析了国内当前具备生物等效性 / I期临床资质的 机构、分布、承担项目能力及生物等效性临床试验机构、药物分析实验室和合同研究组织之间的关系等,对仿制药生物等效性临床试验 研究室的建设内容和规模展开讨论,供业内及监管部门参考。     

具有非齐态生成矩阵罐子模型的渐近性质

研究一种非齐态多臂临床试验的GFU模型,并建立了模型自适应设计.对这种模型,构造了参数的估计量,并获得了相应量的强相合性,收敛速率及其渐近正态性.这些结果对临床试验设计的应用提供了一定的理论依据.     

鼠李糖乳杆菌LGG相关产品的研究进展

LGG作为世界上研究得最多的菌株之一,很多文献报道该菌有各种临床疗效,但随着研究的深入,越来越多经科学设计的人体临床试验得以开展,以前宣称的很多疗效并未在人体试验中得到证实,本综述目的是通过对近年发表的文献进行综述,主要从临床疗效的角度和安全性的角度来阐述论证LGG应用研究的可能性,本文综述了近几年关于LGG疗效的正反两方面的信息,希望能为中国的相关研发单位和企业提供一些风险警示,以防过于乐观地进行相关的药品研发或产业化。     

间充质干细胞治疗新型冠状病毒肺炎研究进展及相关临床试验难点

当前新型冠状病毒肆虐,全球确诊患者超过3 500万例,累计死亡患者超过50万例,对于突发疫情,临床尚缺乏有效特异性治疗,新型冠状病毒已成为危害人类健康、社会发展的主要公共卫生问题。间充质干细胞具有抗炎和免疫调节功能,可降低重症患者体内由冠状病毒引发的细胞因子风暴,改善患者肺部纤维化,促进损伤肺组织修复,有望降低新冠肺炎的死亡率。目前已开展多项间充质干细胞治疗新型冠状病毒肺炎临床试验,初步证实了间充质干细胞应用在新冠肺炎方面的安全及有效性。在间充质干细胞治疗新冠肺炎取得进展的同期,还应看到该疗法独有特点及疫情严峻形势对临床试验开和及评价带来的问题与挑战,包括临床试验方案设计、干细胞质量管理以及治疗中的伦理考量。只有对其加以重视,才能保证在严峻疫情下安全有效地开展间充质干细胞治疗新型冠状病毒肺炎的临床试验。     

基于药物临床试验项目管理系统的临床试验全程管理

我国药物临床试验机构经过多年的发展,临床试验的试验条件质量有了一定的改善,但与发达国家相比,还存在着很多不足,应用信息化管理有助于提高药物临床试验质量管理。文章对医院II～IV期药物临床试验项目管理系统的总体功能进行介绍,该系统从临床试验项目管理出发,结合药物临床试验运行特点及流程,实现临床试验项目及药物全过程化管理,并与医院信息管理系统（HIS）、实验室信息管理系统（LIS）、医学影像信息系统（PACS）接口,构建起机构办、药物管理部门、检验检查科室与研究者之间的公共信息平台,实现了数据共享。     

Poor reporting of scientific leadership information in clinical trial registers

Background

In September 2004, the International Committee of Medical Journal Editors (ICMJE) issued a Statement requiring that all clinical trials be registered at inception in a public register in order to be considered for publication. The World Health Organization (WHO) and ICMJE have identified 20 items that should be provided before a trial is considered registered, including contact information. Identifying those scientifically responsible for trial conduct increases accountability. The objective is to examine the proportion of registered clinical trials providing valid scientific leadership information.

Methodology/Principal Findings

We reviewed clinical trial entries listing Canadian investigators in the two largest international and public trial registers, the International Standard Randomized Controlled Trial Number (ISRCTN) register, and ClinicalTrials.gov. The main outcome measures were the proportion of clinical trials reporting valid contact information for the trials'' Principal Investigator (PI)/Co-ordinating Investigator/Study Chair/Site PI, and trial e-mail contact address, stratified by funding source, recruiting status, and register. A total of 1388 entries (142 from ISRCTN and 1246 from ClinicalTrials.gov) comprised our sample. We found non-compliance with mandatory registration requirements regarding scientific leadership and trial contact information. Non-industry and partial industry funded trials were significantly more likely to identify the individual responsible for scientific leadership (OR = 259, 95% CI: 95–701) and to provide a contact e-mail address (OR = 9.6, 95% CI: 6.6–14) than were solely industry funded trials.

Conclusions/Significance

Despite the requirements set by WHO and ICMJE, data on scientific leadership and contact e-mail addresses are frequently omitted from clinical trials registered in the two leading public clinical trial registers. To promote accountability and transparency in clinical trials research, public clinical trials registers should ensure adequate monitoring of trial registration to ensure completion of mandatory contact information fields identifying scientific leadership     

The quality of registration of clinical trials

Background

Lack of transparency in clinical trial conduct, publication bias and selective reporting bias are still important problems in medical research. Through clinical trials registration, it should be possible to take steps towards resolving some of these problems. However, previous evaluations of registered records of clinical trials have shown that registered information is often incomplete and non-meaningful. If these studies are accurate, this negates the possible benefits of registration of clinical trials.

Methods and Findings

A 5% sample of records of clinical trials that were registered between 17 June 2008 and 17 June 2009 was taken from the International Clinical Trials Registry Platform (ICTRP) database and assessed for the presence of contact information, the presence of intervention specifics in drug trials and the quality of primary and secondary outcome reporting. 731 records were included. More than half of the records were registered after recruitment of the first participant. The name of a contact person was available in 94.4% of records from non-industry funded trials and 53.7% of records from industry funded trials. Either an email address or a phone number was present in 76.5% of non-industry funded trial records and in 56.5% of industry funded trial records. Although a drug name or company serial number was almost always provided, other drug intervention specifics were often omitted from registration. Of 3643 reported outcomes, 34.9% were specific measures with a meaningful time frame.

Conclusions

Clinical trials registration has the potential to contribute substantially to improving clinical trial transparency and reducing publication bias and selective reporting. These potential benefits are currently undermined by deficiencies in the provision of information in key areas of registered records.     

Power gains by using external information in clinical trials are typically not possible when requiring strict type I error control

In the era of precision medicine, novel designs are developed to deal with flexible clinical trials that incorporate many treatment strategies for multiple diseases in one trial setting. This situation often leads to small sample sizes in disease-treatment combinations and has fostered the discussion about the benefits of borrowing of external or historical information for decision-making in these trials. Several methods have been proposed that dynamically discount the amount of information borrowed from historical data based on the conformity between historical and current data. Specifically, Bayesian methods have been recommended and numerous investigations have been performed to characterize the properties of the various borrowing mechanisms with respect to the gain to be expected in the trials. However, there is common understanding that the risk of type I error inflation exists when information is borrowed and many simulation studies are carried out to quantify this effect. To add transparency to the debate, we show that if prior information is conditioned upon and a uniformly most powerful test exists, strict control of type I error implies that no power gain is possible under any mechanism of incorporation of prior information, including dynamic borrowing. The basis of the argument is to consider the test decision function as a function of the current data even when external information is included. We exemplify this finding in the case of a pediatric arm appended to an adult trial and dichotomous outcome for various methods of dynamic borrowing from adult information to the pediatric arm. In conclusion, if use of relevant external data is desired, the requirement of strict type I error control has to be replaced by more appropriate metrics.     

Flexible designs by adaptive plans of generalized Pocock- and O'Brien-Fleming-type and by self-designing clinical trials

Flexible designs are provided by adaptive planning of sample sizes as well as by introducing the weighted inverse normal combining method and the generalized inverse chi-square combining method in the context of conducting trials consecutively step by step. These general combining methods allow quite different weighting of sequential study parts, also in a completely adaptive way, based on full information from unblinded data in previously performed stages. So, in reviewing some basic developments of flexible designing, we consider a generalizing approach to group sequentially performed clinical trials of Pocock-type, of O'Brien-Fleming-type, and of Self-designing-type. A clinical trial may be originally planned either to show non-inferiority or superiority. The proposed flexible designs, however, allow in each interim analysis to change the planning from showing non-inferiority to showing superiority and vice versa. Several examples of clinical trials with normal and binary outcomes are worked out in detail. We demonstrate the practicable performance of the discussed approaches, confirmed in an extensive simulation study. Our flexible designing is a useful tool, provided that a priori information about parameters involved in the trial is not available or subject to uncertainty.     

Maximum likelihood estimation of generalized linear models for adaptive designs: Applications and asymptotics

Due to increasing discoveries of biomarkers and observed diversity among patients, there is growing interest in personalized medicine for the purpose of increasing the well‐being of patients (ethics) and extending human life. In fact, these biomarkers and observed heterogeneity among patients are useful covariates that can be used to achieve the ethical goals of clinical trials and improving the efficiency of statistical inference. Covariate‐adjusted response‐adaptive (CARA) design was developed to use information in such covariates in randomization to maximize the well‐being of participating patients as well as increase the efficiency of statistical inference at the end of a clinical trial. In this paper, we establish conditions for consistency and asymptotic normality of maximum likelihood (ML) estimators of generalized linear models (GLM) for a general class of adaptive designs. We prove that the ML estimators are consistent and asymptotically follow a multivariate Gaussian distribution. The efficiency of the estimators and the performance of response‐adaptive (RA), CARA, and completely randomized (CR) designs are examined based on the well‐being of patients under a logit model with categorical covariates. Results from our simulation studies and application to data from a clinical trial on stroke prevention in atrial fibrillation (SPAF) show that RA designs lead to ethically desirable outcomes as well as higher statistical efficiency compared to CARA designs if there is no treatment by covariate interaction in an ideal model. CARA designs were however more ethical than RA designs when there was significant interaction.     

Confirmatory clinical trials with an adaptive design

Adaptive designs are one of the most promising developments in statistics with applications to clinical trials. Obviously, knowledge at the beginning of a clinical trial will always be limited. Thus it may seem logical that the knowledge from accumulating information should be used to optimize the design of the trial. This paper discusses conditions under which this may be possible in phase III clinical trials where the principal aim is confirmation of hypotheses that have been developed in earlier stages of drug development.     

Clinical and biomarker endpoint analysis in neoadjuvant endocrine therapy trials

Neoadjuvant endocrine therapy trials for breast cancer are now a widely accepted investigational approach for oncology cooperative group and pharmaceutical company research programs. However, there remains considerable uncertainty regarding the most suitable endpoints for these studies, in part, because short-term clinical, radiological or biomarker responses have not been fully validated as surrogate endpoints that closely relate to long-term breast cancer outcome. This shortcoming must be addressed before neoadjuvant endocrine treatment can be used as a triage strategy designed to identify patients with endocrine therapy “curable” disease. In this summary, information from published studies is used as a basis to critique clinical trial designs and to suggest experimental endpoints for future validation studies. Three aspects of neoadjuvant endocrine therapy designs are considered: the determination of response; the assessment of surgical outcomes; and biomarker endpoint analysis. Data from the letrozole 024 (LET 024) trial that compared letrozole and tamoxifen is used to illustrate a combined endpoint analysis that integrates both clinical and biomarker information. In addition, the concept of a “cell cycle response” is explored as a simple post-treatment endpoint based on Ki67 analysis that might have properties similar to the pathological complete response endpoint used in neoadjuvant chemotherapy trials.     

A Bayesian basket trial design that borrows information across strata based on the similarity between the posterior distributions of the response probability

Basket trials simultaneously evaluate the effect of one or more drugs on a defined biomarker, genetic alteration, or molecular target in a variety of disease subtypes, often called strata. A conventional approach for analyzing such trials is an independent analysis of each of the strata. This analysis is inefficient as it lacks the power to detect the effect of drugs in each stratum. To address these issues, various designs for basket trials have been proposed, centering on designs using Bayesian hierarchical models. In this article, we propose a novel Bayesian basket trial design that incorporates predictive sample size determination, early termination for inefficacy and efficacy, and the borrowing of information across strata. The borrowing of information is based on the similarity between the posterior distributions of the response probability. In general, Bayesian hierarchical models have many distributional assumptions along with multiple parameters. By contrast, our method has prior distributions for response probability and two parameters for similarity of distributions. The proposed design is easier to implement and less computationally demanding than other Bayesian basket designs. Through a simulation with various scenarios, our proposed design is compared with other designs including one that does not borrow information and one that uses a Bayesian hierarchical model.     

Adaptive treatment assignment methods and clinical trials.

This paper provides a general review of adaptive experimental designs which utilize accumulating information for assigning the best treatment to the most patients in clinical trials. The historical development of such methods is traced. Though the statistical literture on adaptive designs has developed rapidly and continues to grow, the methods are almost totally unused in practice. An extensive evaluation of why adaptive designs are rarely used in clinical trials is presented. It is asserted that most published methods have important deficiencies that render them unsuitable for application. Suggestions are offered for reorienting this area of research into directions that are potentially more useful for clinical trials.