Minimax and admissible adaptive two-stage designs in phase II clinical trials.
Minimax and admissible adaptive two-stage designs in phase II clinical trials.
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DOI：
10.1186/s12874-016-0194-3
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发表时间：
2016-08-02
影响因子：
4
通讯作者：
Jiang T
中科院分区：
文献类型：
--
作者：
Shan G;Zhang H;Jiang T
Simon的两阶段设计是在第二阶段临床试验的多阶段设计中应用最广泛的，用于在单臂研究中评估新疗法的活性。在这个两阶段设计中，来自第二阶段的样本大小是固定的，而不考虑在第一阶段中观察到的响应数量。通过使用基于条件误差函数的分支定界智能算法，我们为II期临床试验开发了一种新的极小极大自适应设计。我们比较了所提出的设计和竞争对手的性能，包括Simon的Minimax设计，以及允许在无效或有效的情况下提前停止的改进的Simon设计。所提出的极小极大自适应设计的最大样本量保证小于或等于其他已有设计的样本量。当所提出的设计具有与其他设计相同的最大样本量时，它总是具有最小的预期样本量。除了极小极大自适应设计外，我们还引入了从贝叶斯角度确定的允许自适应设计。所提出的自适应极大极小设计可以为临床试验节省样本量。所需的最小样本量对于降低项目成本至关重要。
Simon’s two-stage design is the most widely implemented among multi-stage designs in phase II clinical trials to assess the activity of a new treatment in a single-arm study. In this two-stage design, the sample size from the second stage is fixed regardless of the number of responses observed in the first stage. We develop a new minimax adaptive design for phase II clinical trials, by using the branch-and-bound intelligent algorithm based on conditional error functions. We compare the performance of the proposed design and competitors, including Simon’s minimax design, and a modified Simon’s design that allows early stopping for futility or efficacy. The maximum sample size of the proposed minimax adaptive design is guaranteed to be less than or equal to those from other existing designs. When the proposed design has the same maximum sample size as others, it always has the smallest expected sample size. In addition to the minimax adaptive design, we also introduce admissible adaptive designs determined from a Bayesian perspective. The proposed adaptive minimax design can save sample sizes for a clinical trial. The minimum required sample size is critical to reduce the cost of a project.