Bridging Diversity

Cardiovascular Clinical Trials in the Asia-Pacific Region

This Viewpoint discusses the potential challenges to the operational conduct of clinical trials in the Asia-Pacific region, where there is a high rate of cardiovascular disease, and provides possible solutions.

A Proposal for Post Hoc Subgroup Analysis in Support of Regulatory Submission

BACKGROUND

In clinical trials, it is not uncommon that the primary analysis fails to achieve the study objective for demonstrating the safety and efficacy of a test treatment under investigation, while a specific sub-population analysis shows a significant positive result. In this case, whether the observed positive sub-population analysis results can be used in support of regulatory submission of the test treatment under investigation is an interesting question to both the investigator(s) and the regulatory medical/statistical reviewers.

METHODS

In this article, several statistical evaluations for confirming the integrity and validity of the observed sub-population analysis results were proposed in support of the regulatory submission. Selection bias caused by looking at one subgroup is adjusted before all statistical evaluations, including reproducibility, consistency between sub-population and the entire population, generalizability between the promising sub-population and other sub-populations, and sensitivity index when there are shifts in mean and/or variability between sub-populations. The multiplicity issue is also addressed in measuring generalizability.

RESULTS

A numerical example of a global (multi-regional) clinical trial was presented for illustration purposes. The choice of applying which estimation approach relies on the scale of test statistics. Recommendations for incorporating statistical evaluations in measuring sub-population analysis are provided. Finally, we proposed possible solutions such as real-world data and real-world evidence for regulatory concerns, which may increase the insufficient power.

CONCLUSION

Sub-population analysis can contribute to regulatory submission if it passes the evaluation. This analysis can also support hypothesis generation and the planning of future clinical trials, though it fails to pass the measurement process.

Influence Diagnostics of a Region of Interest in Multi-regional Clinical Trials

Multi-regional clinical trials (MRCTs) are an efficient way to enable recruitment of the planned number of subjects within a reasonable timeframe in drug development for rare diseases. One of the aim of MRCTs is to evaluate the applicability of overall trial results to a region of interest. Various statistical methods proposed for this purpose are primarily relying on regional estimates from subgroup analyses of a region of interest, thus they may not work well for studies with small sample size in rare diseases. This paper, instead, presented how to apply influence diagnostics to assessing influence of a region of interest on the overall results in MRCTs and showed this approach could be an analysis option for MRCTs in rare diseases through Monte Carlo simulation and analysis of an MRCT.

Bayes shrinkage estimator for consistency assessment of treatment effects in multi-regional clinical trials

The primary objective of a multi-regional clinical trial is to investigate the overall efficacy of the drug across regions and evaluate the possibility of applying the overall trial result to some specific region. A challenge arises when there is not enough regional sample size. We focus on the problem of evaluating applicability of a drug to a specific region of interest under the criterion of preserving a certain proportion of the overall treatment effect in the region. We propose a variant of James-Stein shrinkage estimator in the empirical Bayes context for the region-specific treatment effect. The estimator has the features of accommodating the between-region variation and finiteness correction of bias. We also propose a truncated version of the proposed shrinkage estimator to further protect risk in the presence of extreme value of regional treatment effect. Based on the proposed estimator, we provide the consistency assessment criterion and sample size calculation for the region of interest. Simulations are conducted to demonstrate the performance of the proposed estimators in comparison with some existing methods. A hypothetical example is presented to illustrate the application of the proposed method.

Statistical methods for bridging studies

In 1998, the International Conference on Harmonization (ICH) published a guidance to facilitate the registration of medicines among ICH regions including the European Union, the United States, and Japan by recommending a framework for evaluating the impact of ethnic factors on a medicine's effect, such as its efficacy and safety at a particular dosage and dose regimen (ICH E5, 1998). The purpose of ICH E5 is not only to evaluate the ethnic factor influence on safety, efficacy, dosage, and dose regimen, but also more importantly to minimize duplication of clinical data and allow extrapolation of foreign clinical data to a new region. In this article, statistical methods for evaluation of bridging studies based on the concepts of consistency (Shih, 2001), reproducibility/generalizability (Shao and Chow, 2002), the weighted Z-tests for the design of bridging studies (Lan et al., 2005), and similarity between the new and original region based in terms of positive treatment effect (Hsiao et al., 2007) are studied. The relative merits and disadvantages of these methods are compared by several examples.