FDA's Project Optimus initiative for oncology drug development emphasizes selecting a dose that optimizes both efficacy and safety. When an inferentially adaptive Phase 2/3 design with dose selection is implemented to comply with the initiative, the conventional inverse normal combination test is commonly used for Type I error control. However, indiscriminate application of this overly conservative test can lead to substantial increase in sample size and timeline delays, which undermines the appeal of the adaptive approach. This, in turn, frustrates drug developers regarding Project Optimus. The inflation of Type I error depends on the probability of selecting a dose with better long-term efficacy outcome at end of the study based on limited follow-up data at dose selection. In this paper, we discuss the estimation of this probability and its impact on Type I error control in realistic settings. Incorporating it explicitly into the two methods we have proposed result in improved designs, potentially motivating drug developers to adhere more closely to an initiative that has the potential to revolutionize oncology drug development.

翻译：FDA的"Optimus计划"倡议强调在肿瘤药物开发中选择能同时优化疗效与安全性的剂量。为遵循该倡议而实施包含剂量选择的推断性自适应II/III期设计时，通常采用传统的逆正态组合检验来控制I类错误。然而，不加区分地应用这种过于保守的检验方法可能导致样本量大幅增加和研究时间线延迟，从而削弱自适应设计的优势。这反过来会挫伤制药开发者对Optimus计划的积极性。I类错误的膨胀程度取决于：在剂量选择阶段基于有限随访数据，最终在研究结束时选择具有更优长期疗效结果的剂量的概率。本文讨论了在实际场景中该概率的估计及其对I类错误控制的影响。将这一概率明确纳入我们提出的两种方法中，可产生改进的设计方案，有望激励制药开发者更紧密地遵循这项可能革新肿瘤药物开发的倡议。