In rare cancers or subtypes of common cancers, a comparison of multiple promising treatments may be required. The selected treatment can then be assessed against the standard of care (if it exists) or used as a backbone for combinations with new, possibly targeted, agents. There could be different experimental therapies or different doses of the same therapy, and either can be done in combination with standard treatments. A ’pick-the-winner’ design is often used, which focuses on efficacy to select the most promising treatment. However, a treatment with a slightly lower efficacy compared to another treatment may actually be preferred if it has a better toxicity or quality of life profile, is easier to administer, or cheaper. By pre-defining a margin of practical equivalence in order to calculate the sample size, a more flexible assessment can be made of whether the treatments have very different effects or are sufficiently close so that other factors can be used to choose between them. Using exact binomial probabilities, we calculated the sample size for two- and three-arm randomised selection trials including a margin of practical equivalence with a variety of input parameters. We explain conceptually the margin of practical equivalence in this paper, and provide a free user-friendly web application to calculate the required sample size for a variety of input parameters. The web application should help promote the randomised selection design with a margin of practical equivalence, which provides greater flexibility than the ’pick-the-winner’ approach in assessing the results of selection trials.

中文翻译：

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随机二期选择试验中的样本量计算，以实际当量为准

在罕见的癌症或常见癌症的亚型中，可能需要对多种有希望的治疗方法进行比较。然后可以根据护理标准（如果有）评估所选的治疗方法，或用作与新的，可能靶向的药物联合使用的基础。可能会有不同的实验疗法或相同疗法的不同剂量，并且可以与标准疗法联合进行。通常采用“赢家挑剔”设计，该设计着眼于选择最有希望的治疗方法的功效。但是，如果毒性或生活质量更好，更易于管理或更便宜，则实际上比起另一种治疗方法疗效稍低的治疗方法可能更为可取。通过预先定义实际等价的余量来计算样本量，可以更灵活地评估治疗效果是否完全不同或是否足够接近，以便可以使用其他因素进行选择。使用确切的二项式概率，我们计算了两臂和三臂随机选择试验的样本量，其中包括具有各种输入参数的实际当量的余量。我们在本文中从概念上解释了实际等效性的余量，并提供了一个免费的用户友好型Web应用程序来计算各种输入参数所需的样本量。该网络应用程序应在实用等效性的基础上帮助促进随机选择设计，在评估选择试验的结果时，该方法提供了比“成功者”方法更大的灵活性。