A Cautionary Note on Regional Consistency Evaluation With Multiple Primary Endpoints in Multiregional Clinical Trials

In multiregional clinical trials (MRCTs), regional consistency probabilities (RCPs) must be evaluated at the trial design stage in addition to the power for the entire trial population. The Japanese Ministry of Health, Labour and Welfare guidance proposes two widely used criteria for this purpose, referred to as Method 1 and Method 2. While multiplicity adjustment for familywise error rate control is standard practice when multiple primary endpoints are employed, its implications for regional consistency evaluation in MRCTs have not been addressed in the existing literature. In this article, we demonstrate that applying unadjusted consistency thresholds under the Bonferroni procedure leads to monotone inflation of the null RCP with increasing number of endpoints for both Method 1 and Method 2, because the Bonferroni-adjusted critical value progressively selects more extreme overall treatment effect estimates, which in turn inflates the probability of satisfying the regional consistency criterion even when the true treatment effect is absent. To correct for this inflation, we propose adjusted consistency thresholds that restore the null RCP to its single-endpoint reference level, and show that these thresholds can be efficiently obtained via a standard root-finding algorithm. Through numerical studies, we demonstrate that the proposed adjusted thresholds result in only a modest reduction in RCP under the alternative hypothesis, and that thresholds derived under the Bonferroni procedure also prevent null RCP inflation when step-down procedures such as Holm, Hochberg, and Hommel are applied. The methodology is illustrated using a hypothetical MRCT with multiple primary endpoints, and an R package "rcpmcp" implementing all proposed methods is publicly available on GitHub.