药物早期临床试验研究中生物样本收集的考量要点

药物早期临床试验研究是药物研发中非常重要的一部分内容。生物样本是药物早期临床试验研究中获取数据数量最多并且最全面的途径。对生物样本的采集进行科学规范的设计关系到整个药物临床试验的质量。基于此,本文将从生物样本的类型、作用、收集时间及处置等方面开展叙述,明确药物早期临床试验研究中对生物样本收集的考量要点。在此基础上,提高药物早期临床试验研究中所得数据的科学性及可靠性。     

基于医院信息系统的药物临床试验信息系统的构建

为保证药物临床试验质量,加强对临床试验全过程的管理,本机构依托医院现有信息系统构建了药物临床试验信息系统。文中对该系统的设计思路和工作流程进行了阐述,并介绍了该系统在实现临床试验全过程的质量管理和数据溯源方面的优势。同时结合国内临床试验信息系统的现状及本机构建设临床试验信息系统的经验提出了信息化建设中需注意的问题。     

病例报告表的设计及其常见问题分析

病例报告表(Case report form,CRF)是临床试验中收集药物有效性和安全性数据的载体,其设计是否科学严谨直接关系到整个临床试验的成败.本文简介了CRF的设计过程及临床数据采集标准(Clinical data acquisition standards harmonization,CDASH),并对临床试验CRF设计中容易出错的模块和其他常见问题进行分析和说明.     

基于选择性收集安全性数据理念的ICH E19指导原则简介

该文从安全性数据选择性收集的概念、起草制定背景、制定工作进展及主要内容等方面系统介绍国际人用药品注册技术协调会(ICH)《E19:在特定的上市前后期或上市后临床试验中选择性收集安全性数据》,以期为其在中国转化实施提供参考。E19指导原则通过在临床试验中减少收集某些类型的安全性数据收集，从而提高临床试验效率，并有助于减轻申办者和患者负担；但在未来我国落地实施过程中，由于对E19指导原则理解和掌握不充分，可能存在盲目简化数据收集或对安全性数据进行不恰当分析等情况，进而影响患者用药安全或后续药品安全性数据分析和解释等问题，建议设置指导原则实施的过渡期，做好相关各方培训工作，临床试验申办方在使用安全性数据选择性收集方法前应与监管部门沟通并征得其同意。     

药物临床试验记录文件中常见问题及规范实施办法探讨

目的:总结临床试验记录文件中常见的问题,提出规范的文件记录做法,为提高药物临床试验数据记录质量提供参考。方法:参照药物临床试验质量管理规范,结合作者从事药物临床试验质量控制工作的经验,对实际工作中发现的临床试验记录文件中存在的问题进行分析,并探讨符合药物临床试验规范的文件记录做法和相关措施建议。结果:研究者和监察员的综合素质是影响药物临床试验记录文件质量的主要原因。结论:加强对研究者和监察员的试验资质考察、GCP和SOP培训,对临床试验进行项目组、专业组和机构办公室三级质量控制监管,引入国外SMO管理模式、聘请CRC,建立药物临床数据信息化系统是提高药物临床试验记录文件质量的办法。     

多中心临床试验中实验室数据的定性分析方法

目的：探讨多中心临床试验中实验室数据的定性分析方法.方法：通过计算疗前正常者疗后异常的发生率,判断药物对实验室指标的影响;计算疗后实验室检查结果高于疗前者的比例,检验试验结果的随机性.结果：多中心临床试验中实验室定性资料的分析可以抵消年龄、性别、中心间差异的影响,为判定药物的安全性提供重要线索.结论：多中心临床试验中实验室资料既要进行定性分析,又要进行定量分析.     

我国主动终止药物临床试验情况分析

目的 了解我国主动终止的药物临床试验项目的情况以及原因,对主动终止项目的情况进行分析,为提高临床试验效率和受试者权益保护提供借鉴。方法 收集我国药物临床试验登记与信息公示平台中登记的主动终止药物临床试验数据信息,从临床试验概况、临床试验涉及适应症领域分布情况、主动终止的原因以及临床试验实施情况四个方面对登记的主动终止药物临床试验的现状进行分析。结果与结论截至2022-01-12我国药物临床试验登记与信息公示平台共登记15 602项药物临床试验,其中试验状态为主动终止的临床试验共计198项,约占总登记项目的1.3%。其中以化学药品为主(78.2%),生物等效性试验(33.8%),抗肿瘤药物(27.7%)临床试验占比最高,主动终止原因以申办者研发战略调整原因(23.2%)和临床试验失败原因(21.7%)为主,主动终止项目整体国内的平均入组完成率为34.1%。我国新药审评制度改革有力地促进了新药研发的进程,申办者在发起临床试验前应做好充分的准备,提高临床试验效率的同时保护受试者的安全和权益。     

药物临床试验中心实验室的价值与考量

中心实验室是负责临床试验中所采集的样本检测、产生报告和数据的组织.随着多中心临床试验项目数量的增多,中心实验室在药物临床试验中变得愈发重要.本文通过对我院参与的药物临床试验项目采用中心实验室的情况进行分析,探讨中心实验室参与临床试验样本检测工作时需关注的问题,旨在提高临床试验的质量、保障受试者的安全和权益.     

国际多中心临床试验在中国申报和审评状况研究

通过回顾性分析方法,收集、整理和统计近年来在中国申报的国际多中心临床试验的申请项目和审评相关情况.结果显示,近年来国际多中心临床试验申请明显增加,注册申请人主要集中在欧美大型跨国公司,多数药物为新化合物的多中心临床试验,涉及的适应证主要为肿瘤等领域,审评中位时间为7个月.并建议针对药物研发热点的适应证领域合理配置人力资源,加强审评机构、注册审评人与代理机构的沟通,共同提高审评效率.     

对数线性模型在临床试验资料分析中的应用

目的 选择适合药物临床试验列联表资料分析方法,为药物的疗效、安全性和不良反应等提供科学依据.方法 利用对数线性模型,讨论多维列联表分析的优势.结果 与结论临床试验中经常接触到多维列联表的数据,对这类数据需采用特殊的方法进行分析处理.     

How can the emerging patient-centric health records lower costs in pharmacogenomics?

The costs of clinical trials in which the subjects' inherited and somatic genetic variations are taken into consideration are higher than those trials where no genetic data are used. The higher costs are due to increased complexity in exploring clinical and genomic factors, as well as the need to coordinate the various outputs of disparate entities, such as clinical and genetic laboratories, and infer significant associations between genotype and phenotype observations. Environment, diet and lifestyle factors, in addition to clinical data, can all affect a person's response to medicines and thus there is a need to obtain the complete health history of a subject enrolled in a clinical trial in order to assert the right genotype-phenotype associations. Such complete histories can be made available through the emerging patient-centric health records, and challenges concerning these records, such as sustainability, usability and governance, are discussed in this paper.     

An efficient algorithm to determine the optimal two-stage randomized multinomial designs in oncology clinical trials

Sun et al. (2009) proposed an optimal two-stage randomized multinomial design that incorporates both response rate (RR) and early progression rate (EPR) in designing phase II oncology trials. However, determination of the design parameters in their approach requires evaluating huge numbers of combinations among possible values of design parameters, and thus requires highly intensive computation. In this paper we develop an efficient algorithm to identify the optimal two-stage randomized multinomial designs in phase II oncology clinical trials comparing a treatment arm to a control arm. The proposed algorithm substantially reduces the computation intensity via an approximation method. Some other techniques are also used to further improve its efficiency. Examples show that the proposed algorithm has more than a 90% reduction in computation time while having an acceptably low approximation error. This may enhance usage of the optimal two-stage multinomial design in clinical trials and also make it feasible to extend the design to more complicated scenarios.     

The problem of protocol driven costs in pharmacoeconomic analysis.

The increasing number of economic evaluations of healthcare interventions and of drug therapies in particular has been well documented. Surveys of the quality of studies have demonstrated that standards of conduct of such studies have not similarly increased. Concerns over the standards have led to increased calls that economic analyses be more closely linked to randomised controlled clinical trials (RCT). Seven potential threats to the external validity of results limit the generalisability of studies based on RCTs. One such threat is the existence of protocol driven costs. There are two main types of protocol driven costs. Protocol prescribed costs arise as a result of resource use mandated by the clinical trial design. Protocol derived costs occur when increased clinical investigations mandated by trial protocols lead to atypical disease management. Methods to control for protocol driven costs within pharmacoeconomic study designs are available. Modelling studies can be based on data within clinical trials combined with observational data representing more typical resource use. The adoption of pragmatic clinical trial designs provide greater external validity though reduced internal validity. Refinements to explanatory clinical trials can also lead to reduced protocol driven costs. The extent that current studies control for such costs is unclear due to the lack of transparency in the reporting of study methods. A review of published studies found little consideration of protocol driven costs although in several studies there was evidence of their existence. Future studies conducted alongside RCTs should explicitly address how the issue of protocol driven costs was handled within the study framework.     

Unit costs of inpatient hospital days

BACKGROUND: Costs of inpatient days in hospitals are frequently the main drivers of total treatment costs, and their unit cost can markedly affect the outcomes of an economic evaluation. In many countries, the availability of unit cost data is limited and unit costs are often based on data from hospitals participating in clinical trials. OBJECTIVE: To provide data about unit costs of inpatient hospital days in The Netherlands from a healthcare provider's perspective and to give an insight into the extent to which cost categories and total costs differ between hospitals. DESIGN: Unit costs were collected from 22 wards and 11 intensive care units (ICUs) of general and university hospitals involved in clinical trials with 'piggybacked' economic evaluations. Direct costs, such as costs of nursing and medical materials, were calculated by dividing the annual cost per category of the nursing department by the annual number of inpatient days. Indirect costs, such as overheads and accommodation, were allocated to the nursing departments by applying direct allocation. All costs were expressed in 1998 euros (EUR). RESULTS: The mean costs per inpatient day were EUR230 (range: EUR154-EUR311) in general hospitals and EUR323 (range: EUR209-EUR400) in university hospitals. The mean costs per inpatient day in an ICU were EUR1125 (EUR919-EUR1560). Between 38-48% of the total costs were made up of nursing costs. All cost categories showed wide variations between hospitals. CONCLUSIONS: The results of this study were used to develop standard costs for inpatient days in The Netherlands and may contribute to the comparability and generalisability of economic evaluations.     

Development of a placebo effect model combined with a dropout model for bipolar disorder

The aim of this study was to develop a placebo model for bipolar disorder to help optimize clinical trial designs for studies targeting manic episodes in bipolar disorder. A bipolar disease database was built based on individual longitudinal data collected from over 3,000 patients in 11 clinical trials for 5 approved bipolar drugs. An empirical placebo effect model with an exponential decay process plus a linear progression process was developed to quantify the time course of the Young Mania Rating Scale total score based on only placebo data from the database. In order to describe the dropout pattern during the trials, a parametric survival model was developed and the Weibull distribution was identified to be the best distribution to describe the data. Based on the likelihood ratio test, it was found that patients with higher baseline score, slower disease improvement and more rapid disease progression tended to dropout earlier, and the trial features such as trial starting year and trial site were also significant covariates for dropout. A combination of the placebo effect model and the dropout model was applied to simulate new clinical trials through Monte-Carlo simulation. Both the placebo effect model and dropout model described the observed data reasonably well based on various diagnostic plots. The joint placebo response and dropout models can serve as a tool to simulate the most likely level of placebo response with the expected dropout pattern to help design a new clinical trial.     

Health-related quality of life and regulatory issues in the US and Canada

The purpose of this paper is to examine the utilisation of HR-QOL information by US and Canadian federal regulatory bodies, with a focus on pre- and postmarket product review processes. There are a number of challenges facing regulators in using HR-QOL data derived from clinical trials and/or pharmacoeconomic analyses. Some of these challenges are inherent to HR-QOL tools and methodologies, while others relate to their inappropriate application in clinical studies. Regulators also need to take some responsibility for the chasm that exists between the potential and the reality of the contribution of HR-QOL information in decision making. Federal regulators need to develop and promulgate clear guidances that will help improve the quality and validity of studies submitted for review, and greater transparency is needed in terms of how such information is used in the product review process. Advances in technology are sure to increase the volume and complexity of HR-QOL information collected within clinical trials, and regulators need to prepare themselves to address this influx of data. Key actions are proposed to improve both the credibility as well as the uptake of HR-QOL information within the regulatory process so that this important source of information can be used appropriately and to its full potential.     

Pharmacogenomics to predict drug response

From theory to proof-of-concept, pharmacogenomics promises to improve future general healthcare in a number of ways. By identifying individuals who will respond to a particular drug treatment compared to those who have a low probability of response, pharmacogenomic test development hopes to aid the physician in prescribing the optimal medication for each patient. This approach promises faster relief from symptoms, a lowering of side effect risks and a reduction in healthcare costs. Pharmacogenomic tests used by the pharmaceutical companies themselves can be used to help identify suitable subjects for clinical trials, aid in interpretation of clinical trial results, find new markets for current products and speed up the development of new treatments and therapies. This type of approach should also see fewer compounds failing during later phases of development. The questions we are faced with as we enter the new millennium, however, are if and when the promises of pharmacogenomnics in improving healthcare will be fulfilled. Currently, there are only a handful of pharmacogenomic tests and associated products which are commercially available and it remains to be seen what impact these will have on the market and on healthcare in general.     

Comparisons of hypertension-related costs from multinational clinical studies

BACKGROUND: This study identifies and compares the individual cost components of hospital and ambulatory services that manage the care of hypertensive patients in eight countries: the US, the UK, France, Spain, Germany, Italy, Canada and Australia. METHODS: Hypertension-related costs are classified according to four major cardiovascular events: (i) acute myocardial infarction; (ii) congestive heart failure; (iii) stroke; and (iv) renal failure, which was subdivided into renal failure treated by dialysis and renal failure treated by kidney transplantation. To make cross-country costs comparisons, we used the DRG codes used in the US and DRG-like codes from each country. US cost information was obtained from hypertension data available from the literature and health economics researchers. For costs in other countries, we consulted with national health economics experts in each country, used analyses by the Research Triangle Institute, and performed Medline and international literature searches. When available, we obtained information from the countries' public and private nationally representative data sources. For cross-country currency adjustments, all currencies were converted using the Purchasing Power Parities from the Organisation for Economic Cooperation and Development, and then converted into inflation-adjusted year 2000 US dollars. RESULTS: There exists considerable variation in hypertension-related costs from multinational clinical studies. This study documents that costs are generally higher in the US than in other countries; however, this is not always true. In particular, costs of treating heart failure in France and the costs of renal failure without transplantation in Germany and the UK are relatively high. DISCUSSION: While analysing multinational hypertensive cost data, this study also addresses the impact of cross-country cost variations on cost analyses. During the last decade, drug-development researchers have drawn extensively upon multinational trials to resolve enrollment problems and drug-registration issues. At the same time, formulary decision-makers are increasingly demanding multinational cost-effectiveness analyses of the clinical differences found between drug-treatment regimens. Since these data are typically not captured by randomised clinical trials, standard cost estimates must be applied to the clinical trials' resource data, although such standardised calculations do not necessarily account for clinical and cost variations between countries. CONCLUSION: This paper serves as an instrument for identifying which national and event cost data are comparable for analysis as well as highlighting specific problem areas for cost data integration. Although the study focuses on hypertension-related costs, its results may provide insight for multinational cost comparisons of other diseases where similar hospitalisation costs may be analysed.     

临床试验静脉用药调配中心的应用可行性研究

目的:研究临床试验静脉用药调配中心(GCP-PIVAS)的应用可行性。方法:通过举例、回顾性统计分析的方法进行研究。结果:GCP-PIVAS可实现临床试验注射类药品入库、配置、配送记录的电子化溯源,减少配置差错、药物污染,增强职业防护,降低成本,保障药物临床试验数据完整性、规范性及设盲试验的严谨性。结论:GCP-PIVAS保障临床试验注射类药品使用安全,提高机构抗风险能力,对全面提升医院的临床试验管理水平将起到重要作用。     

Inpatient Costs of Major Cardiovascular Events

Objective

Many trials of new therapies for cardiovascular disease include economic measures to assess the impact of treatment on healthcare costs, however, it is difficult to compare results between trials due to variation in methods for assigning costs. Therefore we developed a standard library of inpatient hospital costs for major cardiovascular events commonly reported in trials for new cardiovascular therapies.

Design

Mean and median hospital charges for each event were calculated from Medicare admissions selected by ICD-9-CM codes from the most recent Healthcare Cost and Utilisation Project (HCUP) Nationwide Inpatient Sample (NIS) database available. Charges were converted to costs using the cost-to-charge ratio from the most recent Medicare cost report data and updated to 1999 using a model derived from the Medicare Payment Advisory Commission (MedPAC) forecast to recommend annual updates to Medicare.

Results

Total hospital costs for medical events ranged from $US3654 (1999 values) to $US7833; total hospital costs for surgery and procedures ranged from $US7054 to $US46 317. The distribution of hospital costs is skewed with median costs and lengths of stay lower than mean values. Costs for patients who died in the hospital were generally higher than costs for patients who were discharged.

Conclusions

The library of costs was calculated using a uniform method based on publicly available and easily accessible data and may be updated from year to year. This method provides standardised estimates of hospital costs that can be used in economic analyses of cardiovascular clinical trials.