Department of Statistics, University of Illinois Urbana-Champaign, Champaign, Illinois, USA.
Department of Biostatistics and Programming, Sanofi US, Cambridge, Massachusetts, USA.
Stat Med. 2024 Aug 15;43(18):3383-3402. doi: 10.1002/sim.10129. Epub 2024 Jun 6.
The US FDA's Project Optimus initiative that emphasizes dose optimization prior to marketing approval represents a pivotal shift in oncology drug development. It has a ripple effect for rethinking what changes may be made to conventional pivotal trial designs to incorporate a dose optimization component. Aligned with this initiative, we propose a novel seamless phase II/III design with dose optimization (SDDO framework). The proposed design starts with dose optimization in a randomized setting, leading to an interim analysis focused on optimal dose selection, trial continuation decisions, and sample size re-estimation (SSR). Based on the decision at interim analysis, patient enrollment continues for both the selected dose arm and control arm, and the significance of treatment effects will be determined at final analysis. The SDDO framework offers increased flexibility and cost-efficiency through sample size adjustment, while stringently controlling the Type I error. This proposed design also facilitates both accelerated approval (AA) and regular approval in a "one-trial" approach. Extensive simulation studies confirm that our design reliably identifies the optimal dosage and makes preferable decisions with a reduced sample size while retaining statistical power.
美国 FDA 的 Project Optimus 倡议强调在营销批准前进行剂量优化,这代表着肿瘤药物开发的一个关键转变。它对重新思考可以对传统的关键性试验设计进行哪些改变以纳入剂量优化部分产生了连锁反应。与该倡议一致,我们提出了一种具有剂量优化的新型无缝 II/III 期设计(SDDO 框架)。所提出的设计从随机化设置中的剂量优化开始,进行中期分析,重点关注最佳剂量选择、试验继续决策和样本量重新估计(SSR)。根据中期分析的决策,继续为选定剂量组和对照组招募患者,最终分析将确定治疗效果的显著性。SDDO 框架通过调整样本量提供了更大的灵活性和成本效益,同时严格控制 I 型错误。该设计还通过“一次试验”的方法促进了加速批准(AA)和常规批准。广泛的模拟研究证实,我们的设计可以可靠地确定最佳剂量,并在减少样本量的同时做出更优的决策,保留统计功效。