Chen Kai, Zhou Heng, Lee J Jack, Yuan Ying
Department of Biostatistics and Data Science, The University of Texas Health Science Center, Houston, Texas, USA.
Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
J Biopharm Stat. 2024 Nov 24:1-16. doi: 10.1080/10543406.2024.2429481.
We propose a Bayesian optimal phase 2 design for jointly monitoring efficacy and toxicity, referred to as BOP2-TE, to improve the operating characteristics of the BOP2 design proposed by Zhou. BOP2-TE utilizes a Dirichlet-multinomial model to jointly model the distribution of toxicity and efficacy endpoints, making go/no-go decisions based on the posterior probability of toxicity and futility. In comparison to the original BOP2 and other existing designs, BOP2-TE offers the advantage of providing rigorous type I error control in cases where the treatment is toxic and futile, effective but toxic, or safe but futile, while optimizing power when the treatment is effective and safe. As a result, BOP2-TE enhances trial safety and efficacy. We also explore the incorporation of BOP2-TE into multiple-dose randomized trials for dose optimization, and consider a seamless design that integrates phase I dose finding with phase II randomized dose optimization. BOP2-TE is user-friendly, as its decision boundary can be determined prior to the trial's onset. Simulations demonstrate that BOP2-TE possesses desirable operating characteristics. We have developed a user-friendly web application as part of the BOP2 app, which is freely available at https://www.trialdesign.org.
我们提出了一种用于联合监测疗效和毒性的贝叶斯最优二期设计，称为BOP2 - TE，以改善Zhou提出的BOP2设计的操作特性。BOP2 - TE利用狄利克雷多项分布模型对毒性和疗效终点的分布进行联合建模，基于毒性和无效性的后验概率做出继续/终止决策。与原始的BOP2和其他现有设计相比，BOP2 - TE的优势在于，在治疗有毒且无效、有效但有毒或安全但无效的情况下，能提供严格的I型错误控制，同时在治疗有效且安全时优化检验效能。因此，BOP2 - TE提高了试验的安全性和有效性。我们还探讨了将BOP2 - TE纳入多剂量随机试验以进行剂量优化，并考虑一种将I期剂量探索与II期随机剂量优化相结合的无缝设计。BOP2 - TE对用户友好，因为其决策边界可以在试验开始前确定。模拟结果表明，BOP2 - TE具有理想的操作特性。我们开发了一个用户友好的网络应用程序，作为BOP2应用程序的一部分，可在https://www.trialdesign.org免费获取。
