Selecting promising treatments in randomized Phase II cancer trials with an active control.
Selecting promising treatments in randomized Phase II cancer trials with an active control.
复制标题
在具有主动对照的随机 II 期癌症试验中选择有希望的治疗方法。
DOI：
10.1080/10543400902802425
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发表时间：
2009
影响因子：
1.1
通讯作者：
Cheung,YingKuen
中科院分区：
文献类型：
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作者：
Cheung,YingKuen
II期癌症试验的主要目的是评估新方案在特定类型癌症中的抗肿瘤活性方面的潜在疗效。由于肿瘤治疗的进展和患者人群的异质性，只有在存在活性标准治疗的前瞻性对照组的情况下，才能客观地解释此类评价。本文讨论了II期选择试验的设计问题，其中几个实验方案进行了比较，以积极的控制，目的是确定一个实验组，是更有效的控制或宣布无效，如果没有这样的治疗存在。进行多组随机选择试验是一种有用的策略，当有许多候选药物可用时，可以优先考虑实验性治疗以进行进一步测试，但在这种具有活性对照的试验中所需的样本量可能会引起可行性问题。在这项研究中，我们扩展了序贯概率比检验的正常观察到多臂选择设置。建议的方法允许频繁的中期监测，提供了提前终止试验的高可能性，因此提高了入组的可行性。的终止和选择标准有封闭的形式的解决方案，很容易计算相对于任何给定的一组误差约束。所提出的方法被应用于设计一个选择试验，其中索拉非尼和厄洛替尼的组合相比，在非小细胞肺癌患者中使用肿瘤大小的变化的连续终点的对照组。所提出的方法的操作特性相比，通过模拟的单阶段设计：样本量的要求大大减少，是可行的，在药物开发的早期阶段。
The primary objective of Phase II cancer trials is to evaluate the potential efficacy of a new regimen in terms of its antitumor activity in a given type of cancer. Due to advances in oncology therapeutics and heterogeneity in the patient population, such evaluation can be interpreted objectively only in the presence of a prospective control group of an active standard treatment. This paper deals with the design problem of Phase II selection trials in which several experimental regimens are compared to an active control, with an objective to identify an experimental arm that is more effective than the control or to declare futility if no such treatment exists. Conducting a multi-arm randomized selection trial is a useful strategy to prioritize experimental treatments for further testing when many candidates are available, but the sample size required in such a trial with an active control could raise feasibility concerns. In this study, we extend the sequential probability ratio test for normal observations to the multi-arm selection setting. The proposed methods, allowing frequent interim monitoring, offer high likelihood of early trial termination, and as such enhance enrollment feasibility. The termination and selection criteria have closed form solutions and are easy to compute with respect to any given set of error constraints. The proposed methods are applied to design a selection trial in which combinations of sorafenib and erlotinib are compared to a control group in patients with non–small-cell lung cancer using a continuous endpoint of change in tumor size. The operating characteristics of the proposed methods are compared to that of a single-stage design via simulations: The sample size requirement is reduced substantially and is feasible at an early stage of drug development.