Multiregional Clinical Trials Research Articles

Statistical implications of extrapolating the overall result to the target region in multi-regional clinical trials

The one of the principles described in ICH E9 is that only results obtained from pre-specified statistical methods in a protocol are regarded as confirmatory evidence. However, in multi-regional clinical trials, even when results obtained from pre-specified statistical methods in protocol are significant, it does not guarantee that the test treatment is approved by regional regulatory agencies. In other words, there is no so-called global approval, and each regional regulatory agency makes its own decision in the face of the same set of data from a multi-regional clinical trial. Under this situation, there are two natural methods a regional regulatory agency can use to estimate the treatment effect in a particular region. The first method is to use the overall treatment estimate, which is to extrapolate the overall result to the region of interest. The second method is to use regional treatment estimate. If the treatment effect is completely identical across all regions, it is obvious that the overall treatment estimator is more efficient than the regional treatment estimator. However, it is not possible to confirm statistically that the treatment effect is completely identical in all regions. Furthermore, some magnitude of regional differences within the range of clinical relevance may naturally exist for various reasons due to, for instance, intrinsic and extrinsic factors. Nevertheless, if the magnitude of regional differences is relatively small, a conventional method to estimate the treatment effect in the region of interest is to extrapolate the overall result to that region. The purpose of this paper is to investigate the effects produced by this type of extrapolation via estimations, followed by hypothesis testing of the treatment effect in the region of interest. This paper is written from the viewpoint of regional regulatory agencies.

Regulations and Guidelines for Planning and Design of Multi-regional Clinical Trials

Regulations and Guidelines for Planning and Design of Multi-regional Clinical Trials

Sample size allocation in multiregional equivalence studies.

With the increasing globalization of drug development, the multiregional clinical trial (MRCT) has gained extensive use. The data from MRCTs could be accepted by regulatory authorities across regions and countries as the primary sources of evidence to support global marketing drug approval simultaneously. The MRCT can speed up patient enrollment and drug approval, and it makes the effective therapies available to patients all over the world simultaneously. However, there are many challenges both operationally and scientifically in conducting a drug development globally. One of many important questions to answer for the design of a multiregional study is how to partition sample size into each individual region. In this paper, two systematic approaches are proposed for the sample size allocation in a multiregional equivalence trial. A numerical evaluation and a biosimilar trial are used to illustrate the characteristics of the proposed approaches.

A Re-examination of Japanese Sample Size Calculation for Multi-regional Clinical Trial Evaluating Survival Endpoint

In planning a multi-regional clinical trial including Japan, the sample size for Japanese patients is often considered based on the probability of obtaining a consistent result between Japanese subpopulation and the overall study population, as recommended in the Japanese guideline “Basic Principles on Global Clinical Trials.” We review the commonly used existing method for Japanese sample size calculation based on obtaining a consistent result for survival endpoint. Through simulations, we note that Japanese sample size based on the existing method tended to have less actual power than the nominal power for consistency, especially when there is a large treatment effect. We propose alternative methods based on the delta method and numerical integrations. Our proposed methods give similar Japanese sample sizes, and our simulation studies show that our proposed methods provide the actual power close to the nominal power for consistency.

New Perspective on the Determination of the Number of Japanese Patients in Multiregional Clinical Trials

New Perspective on the Determination of the Number of Japanese Patients in Multiregional Clinical Trials

Identification of Drug Characteristics for Implementing Multiregional Clinical Trials Including Japan

PurposeMultiregional clinical trials (MRCT) are a standard strategy used to improve global drug approval efficiency and the feasibility of clinical trials. Japan is the world's third largest drug market with a unique health care system, making it a key inclusion as an operational region for MRCT (MRCT-JP) for global drug development. We aimed to identify the factors required for efficient drug development by comprehensively reviewing the clinical trials of drugs approved in Japan to identify the factors associated with whether or not MRCT-JP is implemented. MethodsWe surveyed the review reports and summaries of application data published by the Pharmaceuticals and Medical Devices Agency. We identified drugs for which the clinical trial data package included MRCT-JP and selected the same number of drugs for which the clinical trial data package did not include MRCT-JP from the most recent survey period for comparison. We also examined other publication information, in addition to the review reports, as necessary. The influence of each explanatory variable was analyzed by logistic regression analysis, with whether or not MRCT-JP was implemented as the explanatory variable. Statistical significance was set at 5%. FindingsIn the survey period up to September 2017, 165 drugs developed with MRCT-JP were approved for manufacture and sale in Japan. “Respiratory system,” “inhalation,” “biological drug,” and “under review” evaluation status for the United States, European Union, and other areas, “approved” evaluation status for the United States, “new ingredients,” “priority review,” “non-Japanese firm,” and “Top 1–10” and “Top 11–20” drug sales rankings for pharmaceutical companies were identified as potential factors leading to the implementation of MRCT-JP. In contrast, “general anti-infectives for systemic use,” “various,” “external,” “chemical compound,” “unsubmitted” evaluation status for both the United States and European Union, and “Top 51+” drug sales rankings were potential factors for not implementing MRCT-JP. ImplicationsTherapeutic classification and agent type, in addition to capital type and United States and European Union evaluation status suggested by a previous study, were associated with implementing MRCT-JP. It is important to determine the best way to utilize MRCT-JP to maximize the value of products. Our findings were based on successful cases and may therefore be helpful for designing clinical development plans. Appropriate use of MRCT-JP will improve productivity in the pharmaceutical industry.

Use of interval estimations in design and evaluation of multiregional clinical trials with continuous outcomes.

Multiregional clinical trials have been accepted in recent years as a useful means of accelerating the development of new drugs and abridging their approval time. The statistical properties of multiregional clinical trials are being widely discussed. In practice, variance of a continuous response may be different from region to region, but it leads to the assessment of the efficacy response falling into a Behrens-Fisher problem-there is no exact testing or interval estimator for mean difference with unequal variances. As a solution, this study applies interval estimations of the efficacy response based on Howe's, Cochran-Cox's, and Satterthwaite's approximations, which have been shown to have well-controlled type I error rates. However, the traditional sample size determination cannot be applied to the interval estimators. The sample size determination to achieve a desired power based on these interval estimators is then presented. Moreover, the consistency criteria suggested by the Japanese Ministry of Health, Labour and Welfare guidance to decide whether the overall results from the multiregional clinical trial obtained via the proposed interval estimation were also applied. A real example is used to illustrate the proposed method. The results of simulation studies indicate that the proposed method can correctly determine the required sample size and evaluate the assurance probability of the consistency criteria.

Practical Recommendations for Regional Consistency Evaluation in Multi-Regional Clinical Trials with Different Endpoints

ABSTRACTIn recent years, there is an increasing trend to conduct multi-regional clinical trials (MRCT) for drug development in pharmaceutical industry. A carefully designed MRCT could be used in supporting the new drug's approval in different regions simultaneously. The primary objective of an MRCT is to investigate the drug's overall efficacy across regions while also assessing the drug's performance in some specific regions. In order to claim the study drug's efficacy and get drug approval in some specific region(s), the local regulatory authority may require the sponsors to provide evidence of consistency in the treatment effect between the overall patient population and the local region. Usually, the regional specific consistency requirement needs to be pre-specified before the study conduct and the consistency in treatment effect between the region(s) of interest and overall population will be evaluated at the final analysis. In this article, we evaluate the consistency requirements in multi-regional clinical trials for different endpoints, that is, continuous, binary, and survival endpoints. We also compare the different consistency requirements of the same endpoint/measurement if multiple consistency requirements are enforced and our recommendations for each endpoint/measurement will be made based on the comprehensive consideration.

Regional variability and efficient drug development based on ICH E17 guideline; Multi-regional clinical trials

Regional variability and efficient drug development based on ICH E17 guideline; Multi-regional clinical trials

Regional clinical pharmacology trials for Multi-Regional clinical trials.

Regional clinical pharmacology trials for Multi-Regional clinical trials.

On evaluation of consistency in multi-regional clinical trials

ABSTRACTIn recent years, multi-regional clinical trials (MRCT) that conduct clinical trials simultaneously in Asian Pacific region, Europe, and the United States have become very popular for global pharmaceutical development. The main purpose of multi-regional clinical trials is to shorten the time for pharmaceutical development and regulatory submission, and approval around the world. In practice, however, clinical results observed from some regions (sub-population) may not be consistent with the results from other regions and/or all regions combined (entire population). The inconsistency observed may be due to ethnic differences in different regions, differences in medical practice, time points of assessment, or by random chance due to small sample size for the region. Some regional regulatory agencies require consistency evaluation between local country results and overall results. However, the challenge is there is no detailed guidance on the definition of ‘consistency’ and methodology to evaluate it. Therefore, the questions are: how to evaluate consistency and what statistical methods are appropriate to be used for consistency evaluation? In this article, several statistical tests for consistency (similarity) between clinical results observed from a specific sub-population and the entire population are proposed. These methods are compared through extensive simulation. As most published articles discussed consistency evaluation for superiority situations, we have discussed consistency evaluation for non-inferiority situation in this article through a simulated example concerning consistency in some countries. Recommendations of the statistical methods to be used for consistency evaluation are given. Other aspects that should be considered for consistency evaluation are also provided.

Discussion on the Medical Ethics Committee in China from the Perspective of Open Multi-Regional Clinical Trial

Discussion on the Medical Ethics Committee in China from the Perspective of Open Multi-Regional Clinical Trial

Rapid Globalization of Medical Device Clinical Development Programs in Japan - The Case of Drug-Eluting Stents.

Delays in the introduction to the Japanese market of drug-eluting stents (DES) developed overseas (i.e., "device lag") decreased sharply between 2004 and 2012. The reduction accompanied a shift in clinical development from a succession pattern (initial product development and approval overseas followed by eventual entrance into the Japanese market) to parallel development (employing multiregional clinical trials (MRCTs)). Although resource-intensive in the short-term, MRCTs are proving to be an effective tool in simultaneous global product development. Creative study designs and the absence of significant ethnic differences in Japanese subjects regarding DES safety and efficacy and the pharmacokinetic behavior of their coating drugs propel this process. More general factors such as medical need and industry incentivization also encourage this shift. Physicians' preference for DES over other percutaneous coronary interventions, the expanding global DES market, and streamlined development and approval prospects each motivate industry to continue investing in DES product development. The efforts of various stakeholders were also integral to overcoming practical obstacles, and contributions by 'Harmonization by Doing' and a premarket collaboration initiative between the USA and Japan were particularly effective. Today, USA/Japan regulatory cooperation is routine, and Japan is now integrated into global medical device development. MRCTs including Japanese subjects, sites, and investigators are now commonplace.

Sample size determination for a specific region in multiregional clinical trials with multiple co-primary endpoints.

Recently, multi-regional clinical trials (MRCTs), which incorporate subjects from many countries/regions around the world under the same protocol, have been widely conducted by many global pharmaceutical companies. The objective of such trials is to accelerate the development process for a drug and shorten the drug’s approval time in key markets. Several statistical methods have been purposed for the design and evaluation of MRCTs, as well as for assessing the consistency of treatment effects across all regions with one primary endpoint. However, in some therapeutic areas (e.g., Alzheimer’s disease), the clinical efficacy of a new treatment may be characterized by a set of possibly correlated endpoints, known as multiple co-primary endpoints. In this paper, we focus on a specific region and establish three statistical criteria for evaluating consistency between the specific region and overall results in MRCTs with multiple co-primary endpoints. More specifically, two of those criteria are used to assess whether the treatment effect in the region of interest is as large as that of the other regions or of the regions overall, while the other criterion is used to assess the consistency of the treatment effect of the specific region achieving a pre-specified threshold. The sample size required for the region of interest can also be evaluated based on these three criteria.

Some Recent Advances on Statistical Approaches for Planning Multi-regional Clinical Trials

Many multi-regional clinical trials are faced with possible heterogeneity in treatment effect among regions and consequently the interpretation of the trial results is quite challenging. Regional heterogeneity can be caused by the differences in intrinsic factors, extrinsic factors or trial/data quality among regions. An apparent regional difference in treatment effect can be caused by a play of chance or sampling variability. In another aspect, regional heterogeneity may have substantial ramifications on sample size estimation for planning a multi-regional trial, as stipulated in Hung et al. (Pharm Stat 9:173–178, 2010), Lan and Pinheiro (Stat Biosci 14:235–244, 2012) and Quan et al. (Stat Med 33:2191–2205, 2014). Analyses of multi-regional trials are commonly based on a fixed-effect model assuming that the true treatment effects in all regions are equal in magnitude which may or may not be practical. Random-effect modelling has been considered as an alternative to deal with regional heterogeneity. In this research work we shall discuss the statistical implications of the statistical modelling approaches on the type I error probability and statistical power associated with testing the global treatment effect. We also develop formulae to assess the probability that some regions may falsely show an apparent negative trend by chance or sampling variability. As another alternative, a fixed-effect model that accounts for acceptable regional heterogeneity will be introduced.

Revised 'Common Rule' Shapes Protections For Research Participants.

Investigators and institutions have begun to prepare for new federal protections of study participants set to take effect in 2018.

Example-based illustrations of design, conduct, analysis and result interpretation of multi-regional clinical trials

Extensive research has been conducted in the Multi-Regional Clinical Trial (MRCT) area. To effectively apply an appropriate approach to a MRCT, we need to synthesize and understand the features of different approaches. In this paper, examples are used to illustrate considerations regarding design, conduct, analysis and interpretation of result of MRCTs. We start with a brief discussion of region definitions and the scenarios where different regions have differing requirements for a MRCT. We then compare different designs and models as well as the corresponding interpretation of the results. We highlight the importance of paying special attention to trial monitoring and conduct to prevent potential issues associated with the final trial results. Besides evaluating the overall treatment effect for the entire MRCT, we also consider other key analyses including quantification of regional treatment effects within a MRCT, and assessment of consistency of these regional treatment effects.

A nested group sequential framework for regional evaluation in global drug development program

ABSTRACTThe primary objective of a multiregional clinical trial (MRCT) is to assess the efficacy of all participating regions and evaluate the probability of applying the overall results to a specific region. The consistency assessment of the target region with the overall results is the most common way of evaluating the efficacy in a specific region. Recently, Huang et al. (2012) proposed an additional trial in the target region to an MRCT to evaluate the efficacy in the target ethnic (TE) population under the framework of simultaneous global drug development program (SGDDP). However, the operating characteristics of this statistical framework were not well considered. Therefore, a nested group sequential program for regional efficacy evaluation is proposed in this paper. It is an extension of Huang’s SGDDP framework and allows interim analysis after MRCT and in the course of local clinical trial (LCT) phase. It is able to well control the family-wise type I error in the program level and enhances the flexibility of the program. In LCT sample size estimation, we introduce virtual trial, which is transformed from the original program by using discounting factor, and an iteration method is employed to calculate the sample size and stopping boundaries of interim analyses. The proposed sample size estimation method is validated in the simulations and the effect of varied weight, effect size of TE population, and design setting is explored. Examples with normal end point, binary end point, and survival end point are shown to illustrate the application of the proposed nested group sequential program.

Statistical design of noninferiority multiple region clinical trials to assess global and consistent treatment effects

ABSTRACTNoninferiority multiregional clinical trials (MRCTs) have recently received increasing attention in drug development. While a major goal in an MRCT is to estimate the global treatment effect, it is also important to assess the consistency of treatment effects across multiple regions. In this paper, we propose an intuitive definition of consistency of noninferior treatment effects across regions under the random-effects modeling framework. Specifically, we quantify the consistency of treatment effects by the percentage of regions that meet a predefined treatment margin. This new approach enables us to achieve both goals in one modeling framework. We propose to use a signed likelihood ratio test for testing the global treatment effect and the consistency of noninferior treatment effects. In addition, we provide guidelines for the allocation rule to achieve optimal power for testing consistency among multiple regions. Extensive simulation studies are conducted to examine the performance of the proposed methodology. An application to a real data example is provided.

Unified additional requirement in consideration of regional approval for multiregional clinical trials

ABSTRACTTo speed up the process of bringing a new drug to the market, more and more clinical trials are being conducted simultaneously in multiple regions. After demonstrating the overall drug’s efficacy across regions, the regulatory and drug sponsor may also want to assess the drug’s effect in specific region(s). Most of the recent approaches imposed a uniform criterion to assess the consistency of treatment effects between the interested region(s) and the entire study population regardless of the number of regions in multiregional clinical trials (MRCT). As a result, the needed sample size to achieve the desired probability of satisfying the regional requirement could be huge and implausible for the trial sponsors to implement.In this paper, we propose a unified additional requirement for regional approval by differing the parameters in the additional requirement depending on the number of planned regions. In particular, the values of the parameters are determined by a reasonable sample size increase with the desired probability satisfying the additional requirement. Considering the practicality of the global trial or sample size increase, we recommend specific values of the parameters for a different number of planned regions. We also introduce the assurance probability curve to evaluate the performance of different regional requirements.