对多中心临床试验的质量控制要点分析

目前多中心临床试验已经广泛应用于药物上市前、药品上市后的临床研究中.本文归纳分析近年来国内多中心临床试验质量追踪中的问题,阐述保证多中心临床试验质量的关键措施,为提高国内多中心临床试验水平提供参考.     

多中心临床试验中实验室数据的定量分析方法

通过标准差标化法、均数倍数标化法、中位数倍数标化法以及正常值范围标化法等，对不同中心实验室间的差异进行调整，并探讨多中心临床试验中实验室数据的定量分析方法。该方法可以消除中心间差异、性别间差异以及年龄间差异，从而可以对不同中心、性别及年龄组的资料同时进行分析。多中心临床试验中实验室数据的分析必须进行标化，才能进行统一评价。     

多中心临床试验中的中央随机系统研究

目的:加强多中心临床试验管理,提高试验效率,缩短试验周期,减少药物浪费,保障试验质量。方法:利用计算机电话集成(computer telephone integration,CTI)技术,将计算机、电信和网络技术进行集成,成功研发出多中心临床试验中央随机系统并应用于临床试验。结果:多中心临床试验中央随机系统实现了受试者筛选、随机化、药物发放和药物供应链管理等功能。结论:多中心临床试验中央随机系统对跨地域多中心临床试验管理非常有意义。     

复杂网络视角下国际多中心临床试验机构合作趋势探究

目的：挖掘国际多中心临床试验国际合作趋势与特征,在新药研发国际化背景下,为监管部门推动国内多中心临床试验发展提供启示与借鉴。方法：基于美国临床试验注册中心（ClinicalTrials. gov）网站的数据,采集并分析2000—2020年国际多中心临床试验数据,运用复杂网络方法进行数据分析与特征挖掘。结果：自2000—2020年,国际多中心临床试验机构的合作网络规模不断扩大,合作紧密度不断增强,机构合作网络具有无标度特性。结论：国际多中心临床试验合作网络的规模呈扩大趋势,未来国际多中心临床试验机构间合作应该向着加强国际机构间合作紧密度的方向迈进。     

多水平模型在交叉设计临床试验数据分析中的应用

目的:探讨交叉设计临床试验研究中资料的统计分析方法。方法:结合医学临床科研中的实例阐述几种常用的多水平模型(随机系数模型、多水平Logistic模型、多水平Poisson模型)处理临床试验交叉设计资料的原理和方法。结果与结论:多水平模型可以分析交叉设计试验中顺序对试验结果的影响,是处理多中心交叉设计临床试验数据的最有效方法。     

我国眼用制剂临床试验研究现状

目的：探讨国内眼用制剂临床试验研究现状和发展趋势,为我国眼用制剂的研发提供参考。方法：检索收集药物临床试验登记与信息公示平台登记的所有眼用制剂项目信息,采用文献计量学方法,统计临床试验项目登记的剂型与数量、申办者、研究分期、适应证、创新药研发现状、临床试验药物上市情况、国际多中心临床试验等信息,分析国内眼用制剂临床试验的特点。结果：（1）平台共登记了73项临床试验;（2）药物剂型以注射剂及滴眼剂为主;（3）适应证以黄斑水肿、黄斑变性等眼底病变为主;（4）创新药物共有12种（2种为化学药物创新药、10种为生物制品创新药）,8种生物制品通过抗VEGF治疗眼底病变;（5）承担项目数量前3位的申办者中,2个为国内企业,1个为外资企业;（6）除创新药物外,其余24种临床试验相关药物中,有7种药物已完成试验并于国内上市;（7）国际多中心试验共14项,其中由国内企业申办的仅2项。结论：我国眼用制剂的项目数量逐年稳步增长,其中治疗眼底疾病的生物制品为研发热点;国内企业申报项目数量较多,但国内企业发起的国际多中心试验仍需提升。     

我院药物临床试验实施质量回顾性分析

目的:评价我院药物临床试验的实施质量,探讨临床试验实施中的不足,并提出有针对性的改进措施。方法:根据2007-2013年我院药物临床试验项目的质控记录,对照项目实施质量评分标准,分析临床试验质量得分以及各要素的得分情况。并分别对实行和未实行临床研究协调员(CRC)制的A科室和B科室,以及国际多中心和同期国内多中心项目的实施质量进行比较。结果:我院药物临床试验质量得分逐年提高,2013年达90.4分,比2007年增加了1倍;但2013年有3个要素的得分率低于90%,分别为试验实施、试验药物管理和试验记录。A科室项目完成质量得分均高于B科室;2011-2013年A科室的优势要素(得分率差异>15%)显著优于B科室,主要为试验实施(98.8%vs.75.0%)、试验药物管理(100%vs.83.0%)、试验记录(89.9%vs.63.0%)和试验资料管理(100%vs.81.2%),均P<0.01。国际多中心项目实施质量得分高于国内(94.7分vs.83.0分),P<0.01。结论:我院临床试验的薄弱环节主要为试验实施、试验药物管理和试验记录。而CRC制的推广以及国际多中心临床试验的承接是解决以上薄弱环节、提高临床试验质量的有效措施。     

交叉设计多中心临床试验的混合效应模型

目的 :探讨交叉设计多中心临床试验资料的分析方法。方法 :采用混合效应的一般线性模型和混合效应的广义线性模型。结果 :将个体作为随机效应来估计时 ,可以增加误差自由度 ,提高估计精度 ,同时可以考虑中心效应、患者的年龄、性别、基线等协变量的影响 ,并且对于缺失数据在不丢失信息的情况下照样能进行分析。结论 :在交叉设计多中心临床试验资料的分析中 ,混合效应的一般线性模型适用于连续性结果变量的分析 ,混合效应的广义线性模型适用于分类结果变量的分析。     

“全国新药临床试验学术研讨会”通知

由中国药理学会、中国临床药理学与治疗学杂志社、中国新药杂志社联合主办的“全国新药临床试验学术研讨会” ,将于2 0 0 4年 5月 2 8～ 30日在山东省烟台市召开。会议将邀请SFDA新药审评专家、临床研究专家 ,以及国家药品临床研究基地、药厂、新药研究机构、以及国外相关专家作专题报告 ,会议就新药临床试验中的问题进行研讨。一、会议内容1.中国的新药国际多中心临床试验中国药品生物制品检定所　桑国卫院士2 .新药临床试验申报资料中存在的问题SFDA药品审评中心　待定3.国外药物临床研究管理策略分析SFDA药品审评中心　冯　毅部长4 …     

我国儿科人群多中心药物临床试验机构合作关系网络分析

目的：研究我国儿科人群药物临床试验开展情况,分析临床试验机构合作趋势与特征,为我国儿科人群药物临床试验协作网建设提供参考。方法：基于2013—2022年在国家药品监督管理局药品审评中心“药物临床试验登记与信息公示平台”公示的儿科人群药物临床试验项目数据,使用计量分析法和社会网络分析法进行研究特征与合作趋势分析。结果：640项公示项目中,多中心药物临床研究占87.50%(560项);抗肿瘤药及免疫调节剂、血液和造血系统用药是儿童药研发的热门类别;拥有优质临床试验资源的核心机构和核心主要研究者相对集中。结论：我国儿科人群药物临床试验项目逐年增长,部分机构间合作频繁,整体合作网络密度松散,有待进一步加强合作。     

中心效应及中心间样本不均衡对临床疗效评价的影响

目的:本文分析和探讨在多中心临床试验中,中心效应、中心与处理的交互作用以及各中心样本量不均衡对治疗效果评价的影响。方法:以二分类资料两组比较为例,采用计算机模拟试验,分别探讨各中心10种不同样本分配比例、3种中心效应时,对临床疗效的检验效能及Ⅰ类错误的影响。结果:在不存在中心效应,或有中心效应但中心与处理间无交互作用情况下,不同样本量的分配比例对检验效能的影响不大,Ⅰ类错误可控。当中心与处理间存在交互作用时,即使中心间样本量均衡,检验效能也有所下降,Ⅰ类错误亦增加,随着各中心样本均衡性变差,检验效能随之略有降低,I类错误亦随之少许增加。结论:在多中心临床试验中,若中心与处理间存在交互作用,会对疗效评价有影响,而中心间样本均衡性对结果影响较小。在临床试验设计时应给予高度重视。     

Planning and monitoring of placebo-controlled survival trials: comparison of the triangular test with usual interim analyses methods

AIMS: For ethical and economic reasons, interim analysis of phase III clinical trials is essential. This study was conducted to compare the efficiency of two interim analysis procedures, which could be used to allow early termination of a clinical trial. METHODS: We made a post hoc application of two interim analysis methods (Lan & DeMets with O'Brien-Flemming modification, and the triangular test according to Whitehead) by using individual patient data from four published placebo-controlled survival trials. We determined the date the trial would have been stopped had each method been used, and we estimated consequent results in terms of events and patient numbers included in the trial, the duration of the trial, and on treatment effect. RESULTS: The triangular test provided the lowest number of events required to reach a conclusion of the trials while providing an accurate estimate of experimental treatment effects. The triangular test thus indicated the smallest number of patients that would have been enrolled, and the shortest trial duration. The difference between the methods was most important with a detrimental effect of experimental treatment: the number of required events was reduced by 75% and the trial duration was shortened by 48% with the triangular test compared to the Lan & DeMets method. CONCLUSIONS: Stopping a trial early must depend on the clinical context. It is most important to stop a placebo-controlled trial as soon as possible when the experimental treatment can be shown deleterious. In such a situation the triangular test is more appropriate than the Lan & DeMets method. When a treatment effect is no different from, or better than, placebo the triangular test is also superior but the importance of premature termination of the trial in such cases has to be balanced against the inevitable reduction of information that the trial can provide.     

Power and sample size determination for noninferiority trials using an exact method

Noninferiority studies are frequently conducted to justify the development of new drugs and vaccines that have been shown to offer better safety profiles, easier administration, or lower cost while maintaining similar efficacy as compared to the standard treatment. Recently, exact methods have been developed to address the concern that existing asymptotic methods for analyzing and planning noninferiority may fail because of small sample size or because of skewed or sparse data structure. In this paper, we explore the use of exact methods in determining sample size and power for noninferiority studies that focus on the difference of two proportions. The methodology for sample size and power calculations is developed based on an exact unconditional test of noninferiority. We illustrate this exact method using a clinical trial example in childhood nephroblastoma and briefly discuss the optimal sample-size allocation strategy. This exact unconditional method performs very well in various scenarios and compares favorably to its asymptotic counterpart in terms of sensitivity. Therefore, it is a very desirable tool for planning noninferiority trials, especially in situations where asymptotic methods are likely to fail.     

单次口服伐地那非片在健康志愿者的耐受性

目的 观察伐地那非对中国健康男性志愿者的耐受性。方法 用随机、双盲、安慰剂对照、剂量递增试验设计,48名入选者,单次口服5,10,20和40 mg伐地那非分别对比给药前后及各剂量组间受试者的临床症状和实验室化验结果。结果 服药前后,受试者的体征没有显著性变化,组间受试者的体征没有明显差异,试验室检查结果中个别指标虽有统计学意义,但均在正常范围内,无临床意义。结论 受试者对伐地那非5～40 mg的应用剂量具有很好的耐受性,临床推荐1 0～20mg单次服用剂量。     

Nonparametric analysis of covariance for hypothesis testing with logrank and Wilcoxon scores and survival-rate estimation in a randomized clinical trial.

Many clinical trials have time-to-event variables as principal response criteria. When adjustment for covariates is of some importance, the relative role of methods for such analysis may be of some concern. For the Wilcoxon and logrank tests, there is an issue of how covariance adjustment can be nonparametric in the sense of not involving any further assumptions beyond those of the logrank and Wilcoxon test. Also of particular interest in a clinical trial is the estimation of the difference between survival probabilities for the treatment groups at several points in time. As with the Wilcoxon and logrank tests, there is no well known nonparametric way to incorporate covariate adjustment into such estimation of treatment effects for survival rates. We propose a method that enables covariate adjustment for hypothesis testing with logrank or Wilcoxon scores. Related extensions for applying covariate adjustment to estimation of treatment effects are provided for differences in survival-rate counterparts to Kaplan-Meier survival rates. The results represent differences in population average survival rates with adjustment for random imbalance of covariates between treatment groups. The methods are illustrated with a clinical trial example.     

萘替芬酮康唑乳膏治疗足癣209例

目的：观察萘替芬酮康唑乳膏治疗足癣的安全性和疗效。方法：试验按随机双盲对照原则进行。足癣病人随机分成试验组(萘替芬酮康唑乳膏组)和对照组(萘替芬软膏组),均为每日早晚用药1次,于治疗1,2,3,4 wk及停药2 wk随访观察。结果：2组间性别、年龄、病期、病情严重程度积分等各项基础资料比较无显著差异(P＞0.05)。在治疗结束(4 wk)和停药2 wk时2组病人的临床疗效、真菌学疗效和综合疗效的差异无显著意义(P＞0.05)。治疗3 wk时真菌学清除率试验组96.1%,高于对照组的85.7%(P＜0.01),临床和综合疗效试验组均高于对照组(P＜0.05,P＜0.01)。试验组的不良反应发生率为2.4%,对照组为2.8%,2组比较差异无显著意义(P＞0.05)。结论：萘替芬酮康唑乳膏治疗足癣疗效好、安全性高。     

Variable selection for qualitative interactions in personalized medicine while controlling the family-wise error rate

For many years, subset analysis has been a popular topic for the biostatistics and clinical trials literature. In more recent years, the discussion has focused on finding subsets of genomes which play a role in the effect of treatment, often referred to as stratified or personalized medicine. Though highly sought after, methods for detecting subsets with altering treatment effects are limited and lacking in power. In this article we discuss variable selection for qualitative interactions with the aim to discover these critical patient subsets. We propose a new technique designed specifically to find these interaction variables among a large set of variables while still controlling for the number of false discoveries. We compare this new method against standard qualitative interaction tests using simulations and give an example of its use on data from a randomized controlled trial for the treatment of depression.     

Clinical trials and clinical practice: do doctors use the same criteria to judge outcome?

Aims The results of clinical trials often seem to have little influence on the practice of individual doctors. This could be because trial information is presented in the style of a scientific experiment which cannot often be clearly related to the context of everyday patient care. We tested the hypothesis that such framing effects would cause doctors to assess the clinical significance of treatment outcomes differently when presented as clinical trial results rather than as individual patient data.
Methods Fourteen rheumatologists independently reviewed the same 50 sets of data obtained from patients with rheumatoid arthritis. The data consisted of 10 commonly used clinical and laboratory variables measured before and after a period of treatment. The same data were presented in two formats on two separate occasions. The patient data format was a collection of typed sheets attributing each set of results to an individual patient. The clinical trial format was a professionally printed and bound booklet in which each set of results was laid out as summary results of a small uncontrolled clinical trial. Doctors judged the degree of improvement or deterioration and its clinical importance for each data set for both formats. These changes were converted into units of 'Clinical Importance'.
Results Although some statistically significant differences emerged in the individual doctors' judgements between the formats none of these was of a clinically important size. The median of the mean trial—patient difference between the formats for all 14 doctors was 0.035 units of clinical importance [ 95% CI −0.244 to 0.074].
Conclusions This evidence does not support the hypothesis that framing effects are a major cause of the failure of clinical trials to influence clinical practice.     

非虚假设多中心配对临床试验

目的:将配对设计加以扩展,以适应非虚假设和分层。方法:将多中心临床试验的每个中心看作1层,取层样本分数为权计算平均治疗-对照差。将其期望与最小可识别差量比较建立非虚假设,按其方差构造分层配对设计基本关系式,进而推导出样本量公式,检验统计量,和功效函数。将这些用于临床试验的设计、执行和分析。以Monte Carlo方法展示观测功效。结果:这些在最小可识别差量取零时还原为对应经典统计学方法,其观测功效和期望功效吻合,所需样本量小于对应的两组设计。结论:这种临床试验直观高效,适于建立试药对于对照药的临床优效性、非劣效性或等效性,并附有实例描述用法。