An accurately identified maximum tolerated dose (MTD) serves as the cornerstone of successful subsequent phases in oncology drug development. Bayesian logistic regression model (BLRM) is a popular and versatile model-based dose-finding design. However, BLRM with original overdose control strategy has been reported to be safe but "excessively conservative". In this manuscript, we investigate the reason for conservativeness and point out that a major reason could be the lack of appropriate underdose control. We propose designs that balance overdose and underdose control to improve the performance over original BLRM. Simulation results reveal that the new designs have better accuracy and treat more patients at MTD.

翻译：准确确定的最高耐用剂量(MTD)是肿瘤药物开发成功后续阶段的基石。巴伊西亚物流回归模型(BLRM)是一种广受欢迎的多功能模型剂量调查设计。然而,据报告,原剂量过量控制战略的BLRM是安全的,但“过于保守 ” 。在本稿中,我们调查保守的原因,指出一个主要原因可能是缺乏适当的剂量控制。我们提出了平衡过量和剂量不足控制的设计,以提高比原剂量控制机制的性能。模拟结果显示,新设计更加准确,在MTD治疗更多的病人。