Group sequential designs (GSDs) are widely used in confirmatory trials to allow interim monitoring while preserving control of the type I error rate. In the frequentist framework, O'Brien-Fleming-type stopping boundaries dominate practice because they impose highly conservative early stopping while allowing more liberal decisions as information accumulates. Bayesian GSDs, in contrast, are most often implemented using fixed posterior probability thresholds applied uniformly at all analyses. While such designs can be calibrated to control the overall type I error rate, they do not penalise early analyses and can therefore lead to substantially more aggressive early stopping. Such behaviour can risk premature conclusions and inflation of treatment effect estimates, raising concerns for confirmatory trials. We introduce two practically implementable refinements that restore conservative early stopping in Bayesian GSDs. The first introduces a two-phase structure for posterior probability thresholds, applying more stringent criteria in the early phase of the trial and relaxing them later to preserve power. The second replaces posterior probability monitoring at interim looks with predictive probability criteria, which naturally account for uncertainty in future data and therefore suppress premature stopping. Both strategies require only one additional tuning parameter and can be efficiently calibrated. In the HYPRESS setting, both approaches achieve higher power than the conventional Bayesian design while producing alpha-spending profiles closely aligned with O'Brien-Fleming-type behaviour at early looks. These refinements provide a principled and tractable way to align Bayesian GSDs with accepted frequentist practice and regulatory expectations, supporting their robust application in confirmatory trials.

翻译：组序贯设计（GSDs）在确证性试验中被广泛采用，以在保持I类错误率控制的前提下实现期中监测。在频率学派框架中，O'Brien-Fleming型终止边界在实践中占主导地位，因其在试验早期施加高度保守的终止标准，同时允许随着信息积累而采用更宽松的决策标准。相比之下，贝叶斯GSDs通常采用固定的后验概率阈值，并在所有分析时点统一应用。虽然此类设计可通过校准控制整体I类错误率，但由于未对早期分析施加惩罚，可能导致显著更激进的早期终止。这种行为可能引发过早结论和治疗效应估计膨胀的风险，对确证性试验造成隐患。本文提出两种可实际实施的改进方案，以恢复贝叶斯GSDs中保守的早期终止特性。第一种方案构建了后验概率阈值的两阶段结构：在试验早期阶段采用更严格的标准，后期则放宽标准以保持检验效能。第二种方案将期中分析的后验概率监测替换为预测概率准则，该准则天然考虑未来数据的不确定性，从而有效抑制过早终止。两种策略仅需一个额外的调优参数，且均可高效校准。在HYPRESS研究设定中，两种方法均较传统贝叶斯设计获得更高检验效能，同时在早期分析时产生与O'Brien-Fleming型行为高度一致的α消耗曲线。这些改进为贝叶斯GSDs与主流频率学派实践及监管期望的对接提供了原则性且可操作的路径，支持其在确证性试验中的稳健应用。